Energy storage has become a fundamental component in renewable energy systems, especially those including batteries. However, during the charging and the discharging process, there are some parameters that are not controlled by the user. That uncontrolled working leads to aging of the batteries and a reduction of their life cycle. Therefore, it causes an early replacement. Different control methods have been developed with the goal of protecting the battery and extending its life expectancy, being the most used the constant current-constant voltage. However, several studies show that charging time can be reduced by using Fuzzy Logic Control or Model Predictive Control. Other benefits are; temperature control and an extension of life expectancy. For all these reasons, FLC and MPC have proven to be more efficient than traditional charge control methods.

This paper attempts to alter a prevailing assumption that buildings use energy to an understanding that in fact, people use energy. Therefore, to successfully accelerate the transition to a low-carbon society and economy more emphasis should be on motivating people and increasing their awareness by making them energy conscious building users and therefore active players in the energy transition process. In this context, this paper provides insights from the Horizon 2020 MOBISTYLE project. It demonstrates research and development approaches, highlights the main project objectives, and presents findings of an ethnographic (qualitative) study of users’ habits, practices, and needs. The aim of the project is to motivate behavioural change by raising consumer awareness through the provision of attractive personalized information on user’s energy use, indoor environment and health, all enabled by an integrated information and communication technology (ICT) service. In this context, the anthropological people-centred approach is integrated into the MOBISTYLE approach putting users at the centre of the ICT tools development process. The main quantitative objective of the project is a reduction of energy use for at least 16 % prompted by the provision of combined information and feedback systems on energy, indoor environmental quality (IEQ) and health. The most relevant motivational factors and key performance indicators (KPIs) for encouraging a more energy conscious and healthy lifestyle were defined by means of a people-centred approach, adopting anthropological inquiries in different settings. Information about users’ lifestyles and their needs was collected in focus groups with potential users in five case studies, located in different European Union (EU) countries. Behaviour change is achieved through awareness campaigns, which encourage users to be pro-active about their energy consumption and to simultaneously improve health and well-being.

The RPL protocol is a routing protocol for low power and lossy networks. In such a network, energy is a very scarce resource; so many studies are focused on minimizing global energy consumption. End-to-end latency is another important performance indicator of the network, but existing research tends to focus more on energy consumption and ignore the end-to-end delay of data transmission. In this paper, we propose a kind of energy equalization routing protocol to maximize the surviving time of the restricted nodes so that the energy consumed by each node is close to each other. At the same time, a multi-path forwarding route is proposed based on the cache utilization. The data is sent to the sink node through different parent nodes at a certain probability, not only by selecting the preferred parent node, thus avoiding buffer overflow and reducing end-to-end delay. Finally, the two algorithms are combined to accommodate different application scenarios. The experimental results show that the proposed three improved schemes improve the reliability of the routing, extend the lifetime of the network, reduce the end-to-end delay, and reduce the number of DAG reconfiguration.

The perovskite crystal structure has garnered significant attention due to its unique properties and potential applications. Particularly, YTiO3 is a ferromagnetic Mott insulator with strong electron correlation effects and orbital ordering, so it is a good candidate for electronic applications. In this research, we investigate the structural, elastic, and electronic properties of Y1-xSrxTiO3 (x=0.01, 0.10, 0.50, 0.99) perovskites within the Pm3m space group using density functional theory (DFT) to improve mechanical properties while preserving electronic properties. Initial geometry optimizations were performed using the GGA-PBE functional with a 6×6×6 Monkhorst-Pack k-point mesh. The study utilized the CASTEP code with ultrasoft pseudopotentials for DFT calculations. Complete structural relaxations were achieved, and the elastic constants which confirm the mechanical stability of the materials were determined using the finite strain theory. The electronic properties were analyzed through band structure and partial density of states (PDOS) calculations. Despite variations in band structures due to Sr doping, no bandgap was observed, indicating the metallic nature of the compounds. The study highlights that p and d orbitals are predominant in electronic states. The findings suggest that Sr doping significantly influences the elastic properties, making these materials potentially valuable for various applications requiring robust mechanical properties.

This study considers ways to increase the consumption of sustainable fashion, given the significant environmental and social damages, associated with the industry. A series of experiments were conducted examining the impacts of choice architecture (nudges) under field conditions in collab-oration with one of Israel’s largest shopping centers. The study sought to identify which inter-ventions at the retail level successfully motivate sustainable fashion behavioral change regarding purchases and willingness to pay more, along with agreement with several statements regarding the climate crisis and sustainable fashion. Among the types of nudges examined in this field study were providing information, increasing accessibility to sustainable alternatives and appealing to social identity, in relation to demographics and green self-image. The study found that offering alterna-tives to consumers constitutes the most effective way to “nudge” consumers toward more sus-tainable purchasing behavior. Nonetheless, this does not negate the contribution of providing in-formation and strengthening social norms regarding sustainable fashion. Additionally in all groups, most participants reported that they do not know how to distinguish between sustainable and non-sustainable fashion, nor do they believe that the clothes they purchased were actually sustainable. The findings emphasize the need for policies that will increase the accessibility of sustainable fashion.

Variance-driven decomposition based on the singular spectrum analysis of the European Project for Ice Coring in Antarctica (EPICA) dD, CO2 and CH4 records allowed a novel quantitative structural interpretation of all glacial/interglacial cycles and glacial terminations of the last 800 kyr. This bottom-up approach used the response components of EPICA stacked records to reconstruct the envelope of the thermal response through a physical interference model. The aim was to improve the understanding regarding the features of intensity, amplitude, and asymmetry of 73 marine isotope stages (MIS) and seven terminations. The Antarctic stack record can be described by a variance-weighted interference model of ten thermal waves of different origins (mid-term oscillation, orbitals and suborbitals) that stochastically interfere at a given time according to their relative differences in frequency, intensity, and polarity. Interglacial/glacial stages resulted from constructive interference and bipolar amplification of warming/cooling responses, respectively. The low intensity MISs (including 90% of substages) and the unbiased-dated terminations fell in the low interference regions where dominant destructive patterns minimise the thermal envelope. The positive skewness of the EPICA stack resulted from the constructive interference with a strong bias in the warming direction, especially after the Mid-Brunhes Event. Duration analysis of short eccentricity hemicycles exhibited an intrinsic unexpectedly prolonged mean cooling in the nominal solution (5.8 kyr) and its EPICA response as well (8.6 kyr), along with an interference-induced asymmetry (21.1 kyr). The overall effect resulted in the saw-tooth shape of glacial cycles which is heavily induced by interference and related to the intermediate feedback mechanisms controlled by short eccentricity.

With the widespread Application of Virtual Reality (VR) in education, optimizing foreign language learning in VR has become a focal point of research. This paper introduces a comprehensive theoretical framework (VR-CCL) based on constructivism and cognitive load theory to enhance foreign language learning in VR. Through a literature review, we explore the applications of VR in education, foreign language learning theories, and prior works on technology-assisted language learning. We further detail the three main components of the VR-CCL framework and validate its effectiveness through two case studies: Duolingo VR and Rosetta Stone VR. Finally, we discuss the strengths and limitations of the framework and its implications for educators and developers.

The gauge field equation for fluid mechanics established in Part 1 is developed into a first-order scattering theory in the simplified case of a two-dimensional incompressible flow over a flat plate. This is used to present a model for the origin of Tollmien-Schlichting (TS) waves based on scattering between fluid particles. As a result, analytical formulae for the maximum amplification factor and the transition point from laminar to turbulent flow in the boundary layer are obtained. The mathematical transformations from the stationary field equations in Part 1 to a scattering theory with time evolution along the flow axis using Wick rotation are elaborated in detail.

Digital health research is an emerging discipline that requires easy-to-understand theoretical frameworks and implementation models for digital health providers in health and social care settings. The COVID-19 pandemic has heightened demand for digital health discipline-specific instruction on ‘how to’ manage evidence-based digital health transformation. Access to the use of these models guarantees that digital health providers can investigate phenomena using safe and suitable approaches and methods to conduct research and identify answers to challenges and problems that arise in health and social care settings. The COMPASS theory is designed to aid transformation of health and social care environments. A navigational rose of primary quadrants is divided by four main compass points, with person-centred care being central to the philosophy. Two axes produce Cartesian planes that intersect to form a box plot, which can be used to discover human and physical resource weightings to augment digital health research design and implementation. A third continuum highlights stakeholders' capabilities, critical for any multidisciplinary study. The COMPASS mnemonic guides end-users through the process of design, development, implementation, evaluation, and communication of digital health transformations. The theory's foundations are presented and explained in context of the 'new normal' of health and social care delivery.

We introduce the Symplectic Structure of Information Geometry based on Souriau’s Lie Group Thermodynamics model, with a covariant definition of Gibbs equilibrium via invariances through co-adjoint action of a group on its moment space, defining physical observables like energy, heat, and moment as pure geometrical objects. Using Geometric (Planck) Temperature of Souriau model and Symplectic cocycle notion, the Fisher metric is identified as a Souriau Geometric Heat Capacity. Souriau model is based on affine representation of Lie Group and Lie algebra that we compare with Koszul works on G/K homogeneous space and bijective correspondence between the set of G-invariant flat connections on G/K and the set of affine representations of the Lie algebra of G. In the framework of Lie Group Thermodynamics, an Euler-Poincaré equation is elaborated with respect to thermodynamic variables, and a new variational principal for thermodynamics is built through an invariant Poincaré-Cartan-Souriau integral. The Souriau-Fisher metric is linked to KKS (Kostant-Kirillov-Souriau) 2-form that associates a canonical homogeneous symplectic manifold to the co-adjoint orbits. We apply this model in the framework of Information Geometry for the action of an affine Group for exponentiel families, and provide some illustrations of use cases for multivariate Gaussian densities. Information Geometry is presented in the context of seminal work of Fréchet and his Clairaut-Legendre equation. Souriau model of Statistical Physics is validated as compatible with Balian gauge model of thermodynamics. We recall the precursor work of Casalis on affine group invariance for natural exponential families.

An association between subtle changes in T2 white matter hyper-intense signals (WMHS) de-tected in fetal brain magnetic resonance imaging (fbMRI) and congenital cytomegalovirus (CMV) infection has been established. The research aim of this study is to compare children with congenital CMV infection with neurodevelopment outcome and hearing deficit with and with-out WMHS in a prospective historic cohort of 58 fbMRIs. Of these, WMHS was detected in 21. The median infection week of the WMHS group was earlier than the normal fbMRI group (8 and 17 weeks of gestation respectively). The proportion of infants treated with valganciclovir in the WMHS group was distinctly higher. Hearing impairment was not significantly different be-tween the groups. VABS scores in all 4 domains were within normal range in both groups. The median score of the motor skills corrected for week of infection was better in the WMHS group. A multivariate analysis using week of infection interaction variable of WMHS and valganciclo-vir treatment showed better motor score outcomes in the valganciclovir treatment group despite earlier week of infection. WMHS was not associated with neurodevelopmental outcome and hearing deficit. In our cohort valganciclovir treatment may have a protective effect on fetuses with WMHS by improving neurodevelopment outcome.

Background: There are major air pollution monitoring gaps in sub-Saharan Africa. Developing capacity in the region to conduct air monitoring in the region can help estimate exposure to air pollution for epidemiology research. The purpose of our study is to develop a land use regression (LUR) model using low-cost air quality sensors developed by a research group in Uganda (AirQo). Methods: Using these low-cost sensors, we collected continuous measurements of fine particulate matter (PM2.5) between May 1, 2019 and February 29, 2020 at 22 monitoring sites across urban municipalities of Uganda. We compared average monthly PM2.5 concentrations from the AirQo sensors with measurements from a BAM-1020 reference monitor operated at the US Embassy in Kampala. Monthly PM2.5 concentrations were used for LUR modeling. We used eight Machine Learning (ML) algorithms and ensemble modeling; using 10-fold cross validation and root mean squared error (RMSE) to evaluate model performance. Results: Monthly PM2.5 concentration was 60.2 µg/m³ (IQR: 45.4-73.0 µg/m³; median= 57.5 µg/m³). For the ML LUR models, RMSE values ranged between 5.43 µg/m³ - 15.43 µg/m³ and explained between 28% and 92% of monthly PM2.5 variability. Generalized additive models explained the largest amount of PM2.5 variability (R²=0.92) and produced the lowest RMSE (5.43 µg/m³) in the held-out test set. The most important predictors of monthly PM2.5 concentrations included monthly precipitation, major roadway density, population density, latitude, greenness, and percentage of households using solid fuels. Conclusion: To our knowledge, ours is the first study to model the spatial distribution of urban air pollution in sub-Saharan Africa using air monitors developed from the region itself. Non-parametric ML for LUR modeling performed with high accuracy for prediction of monthly PM2.5 levels. Our analysis suggests that locally produced low-cost air quality sensors can help build capacity to conduct air pollution epidemiology research in the region.

Dissemination of resistant pathogens via food supply chains is a notable public health danger from farm to fork. The proposed work analysed the distribution of E. coli among various sources of animal-based food supply chain. Overall, 500 samples were heaped up from livestock, poultry sectors, environment, fisheries, and dairy. Standard microbiological procedures were used to isolate and identify E. coli. Further, isolates were confirmed by using MALDI-TOF and virulence associated genes (VAGs). The phenotypic resistance pattern of the isolates was determined by molecular identification of antibiotic resistance genes (ARGs) through PCR using specific primers. Shiga toxin producing E. coli (STEC) were subjected to PCR based O typing using specific primers against different O types. Overall results revealed that 154 (30.5%) samples were confirmed as E. coli, in which77 (50%) isolates were MDR E. coli. Among these, total 52 (67.53%) isolates showed array of VAGs in which 21 (40.38%) were confirmed as STEC based on stx1 and stx2. Furthermore, 12/52 (23.07%) isolates were detected as Non-O157 STEC co-harboring mcr-1 and blaNMD-1. Overall, O26 STEC was found to be the most prevalent among different non-O157 types. Herein, results proposed that detection of such STEC MDR E. coli causing serious public health consequences in developing countries.

HU is the Hypergeometrical Universe Theory (HU)[1-8], proposed in 2006, where the Universe is a Lightspeed Expanding Hyperspherical Hypersurface and Gravitation is an absolute-velocity-dependent, epoch-dependent force. Here we introduce the Big Pop Cosmogenesis and show our calculations associated with the Equation of State of the Universe. This article is the first in a series of articles[9-22] supporting the paradigm shift.

A study of Bianchi Type I cosmological model is undertaken in the framework of creation of particles. To accommodate the creation of new particles, the universe is regarded as an Open thermodynamical system. The energy conservation equation is modified with the incorporation of a creation pressure in the energy momentum tensor. Exact solutions of the field equations are obtained (i) for a particular choice of the particle creation function and (ii) by considering the deceleration parameter to be constant. In the first model the behavior of the solution at late times is investigated. The physical aspects of the model have also been discussed. In the case of the second model we have restricted our analysis to the power law behaviour for the average scale factor. This leads to a particular form for the particle creation function. The behavior of the solution is investigated and the physical aspects of the model have also been discussed for the matter dominated era.

The cosmological relevance of emptiness—that is, space without bodies—is not yet sufficiently appreciated in natural philosophy. This paper addresses two aspects of cosmic emptiness from the perspective of natural philosophy: the distances to the stars in the closer cosmic environment and the expansion of space as a result of the accelerated expansion of the universe. Both aspects will be discussed from both a historical and a systematic perspective. Emptiness can be interpreted as “coming” in a two-fold sense: Whereas in the past knowledge of emptiness as it were came to human beings, in the future it is coming insofar as its relevance in the cosmos will increase.The longer and more closely emptiness was studied since the beginning of modernity, the larger became the spaces over which it was found to extend. From a systematic perspective, I will show with regard to the closer cosmic environment that the earth may be separated from the perhaps habitable planets of other stars by an emptiness that is inimical to life and cannot be traversed by humans. This assumption is a result of the discussion of the constraints and possibilities of interstellar space travel as defined by the known natural laws and technical means. With the accelerated expansion of the universe, the distances to other galaxies (outside of the so-called local group) are increasing. According to the current standard model of cosmology and assuming that the acceleration will remain constant, in the distant future this expansion will lead first to a substantial change in the epistemic conditions of cosmological knowledge and finally to the completion of the cosmic emptiness and of its relevance, respectively. Imagining the postulated completely empty last state leads human thought to the very limits of what is conceivable.

Integrated energy systems (IES) seek to minimize power generating costs in future power grids through the dynamic coupling of different energy technologies. To accommodate fluctuations in load demand due to the penetration of renewable energy sources, flexible operation capabilities must be fully exploited, i.e., even power plants that are traditionally considered as base-load units need to be operated according to unconventional paradigms. Thermomechanical loads induced by frequent power adjustments can accelerate the wear and tear of components. If a unit is flexibly operated without respecting limits on materials and components, the risk of failures of expensive components will eventually increase, nullifying the additional profits ensured by flexible operation. In addition to the limits on power variations (explicit constraints), the solution of the unit dispatch problem needs to meet the limits on temperature, pressure and flow rate variations (implicit constraints). The FARM (Feasible Actuator Range Modifier) module was developed to enable existing optimization algorithms to identify solutions to the unit dispatch problem that are both economically favorable and technologically sustainable. Thanks to the iterative dispatcher-validator scheme, FARM permits addressing all the imposed constraints without excessively increasing the computational costs. In this work, the algorithms constituting the module are described, and the performance was assessed by solving the unit dispatch problem for an IES composed of three units, i.e., Balance of Plant, Gas Turbine, High-Temperature Steam Electrolysis. Finally, FARM module provides dedicated tools for visualizing the response of the process variables of interest during operation transients and a tool aiding the operator at making decisions. These techniques might represent the first step towards the deployment of an Ecological Interface Design (EID) for IES units.

The ankle is a complex joint with a high injury incidence. Rehabilitation Robotics applied to the ankle is a very active research field. We present cable-driven reconfigurable robot kinematics and statics. We studied how the tendons pull mid-foot bones around the talocrural and subtalar axes. Likewise, we propose a hybrid serial-parallel mechanism analogous to the ankle. Then, using screw theory, we synthesized a cable-driven robot with the human ankle in the closed-loop kinematics. We incorporate a draw-wire sensor to measure the axes’ pose and compute the product of exponentials. We reconfigure the cables to balance the tension and pressure forces using the axis projection on the base and platform planes. Likewise, we also computed the workspace to show that the reconfigurable design fits several sizes. The data used is from anthropometry and statistics. Finally, we validated the robot’s statics with MuJoCo for various cable length groups corresponding to the axes’ range of motion. We suggested a platform adjusting system and an alignment method. The design is lightweight, and the cable-driven robot has advantages over rigid parallel robots, such as Stewart platforms. We will use compliant actuators.

VNREDSat-1 is the first Vietnamese satellite allowing the survey of environmental parameters such as vegetation and water coverages, or surface water quality at medium spatial resolution (from 2.5 to 10 meters depending on the considered channel). The NAOMI sensor on board VNREDSat-1 has the required spectral bands to assess the suspended particulate matter concentration, SPM. Because recent studies have shown that the remote sensing reflectance, Rrs(), at the blue (450 – 520 nm), green (530 – 600 nm), and red (620 – 690 nm) spectral bands can be assessed from NAOMI with a good accuracy, the present study is dedicated to the development and validation of an algorithm (hereafter referred to as V1SPM) to assess SPM from Rrs() over inland and coastal waters of Vietnam. For that purpose, an in situ data set of hyper-spectral Rrs() and SPM (from 0.47 to 240.14 g.m-3) measurements collected at 205 coastal and inland stations has been gathered. Among the different approaches, including 4 historical algorithms, the polynomial algorithms involving the red-to-green reflectance ratio presents the best performance on the validation data set (MAPD of 18,7%). Compared to the use of a single spectral band, the band ratio allows to reduce the scatter around the polynomial fit as well as the impact of imperfect atmospheric corrections. Due to the lack of matchup data points with VNREDSat-1, the full VNREDSat-1 processing chain (RED-NIR and V1SPM) aiming at estimate SPM from the top-of-atmosphere signal has been applied to the Landsat-8/OLI match-up data points with relatively low to moderate SPM concentration (3.33-15.25 g.m-3) showing a MAPD of 15,8%. An illustration of the use of this VNREDSat-1 processing chain during a flooding event occurring in Vietnam is provided.

Progress in laser-driven proton acceleration requires increasing the proton maximum energy and laser-to-proton conversion efficiency, while reducing the divergence of the proton beam. However, achieving all these qualities simultaneously has proven challenging experimentally, the increase in beam energy often coming at the cost of beam quality. Numerical simulations suggest that coupling multi-PW laser pulses with ultrathin foils could offer a route for such simultaneous improvement. Yet experimental investigations have been limited by the scarcity of such lasers and the need for very stringent temporal contrast conditions to prevent premature target expansion before the pulse maximum. Here, combining the newly commissioned Apollon laser facility that delivers high-power ultrashort (∼24fs) pulses, with a double plasma mirror scheme to enhance its temporal contrast, we demonstrate the generation of up to 35 MeV protons with only 5 J of laser energy. This approach also achieves improved laser-to-proton energy conversion efficiency, reduced beam divergence, and optimized spatial beam profile. Therefore, despite the laser energy losses induced by the plasma mirror, the proton beams produced by this method are enhanced on all accounts compared to those obtained under standard conditions. Particle-in-cell simulations reveal that this improvement results from the intensified electrostatic field caused by a more compact hot-electron distribution.

This paper is devoted to an accurate determination of the London dispersive and polar free energy of adsorption, the two Lewis acid γs+ and base γs- components of polar surface energy γsAB of 2D single-crystalline and polycrystalline covalent organic frameworks such as TAPPy-TPA-COFs. Inverse gas chromatography (IGC) at infinite dilution was used to quantify the different surface parameters of the different materials. From IGC measurements, one determined the net retention time of the adsorption of n-alkanes and several polar solvents on single-crystalline and polycrystalline covalent organic frameworks. The free surface Gibbs energy of adsorption was obtained for the various organic molecules at different temperatures from their net retention volume values. The separation between the London dispersive energy and the polar energy of adsorbed molecules was carried out by using a new thermodynamic parameter PSX chosen as new indicator variable and taken into account the deformation polarizability and the harmonic mean of the ionization energies of solvents and solid materials, derived from London dispersion equation. The obtained results are very promising for the accurate determination of the surface thermodynamic parameters of adsorption of organic solvents on solid surfaces.

Researchers are always looking to find ways to use energy more efficiently while keeping people comfortable at home. They've tried different methods like fuzzy logic and genetic algorithms to do this. In this paper, we introduce a novel model that combines different techniques like data smoothing, optimization, machine learning, and control algorithms to reach this goal in smart homes. The proposed model is made up of three main parts: smoothing, optimization, and control. The smoothing part uses the Kalman filter to get rid of any unnecessary noise and make sure the data used to predict energy use is clean and smooth. The optimization part uses both genetic with firefly algorithms and artificial neural networks to minimize the gap between the actual environmental conditions and the conditions users find comfortable. It adjusts the comfort settings in real-time using machine learning. The control part uses Mamdani fuzzy logic to make sure energy is delivered in the best way possible to the systems that control temperature, lighting, etc., making the home comfortable and saving energy at the same time. Comparative analyses demonstrate the superiority of the proposed model over existing algorithms, including the Particle Swarm Optimization (PSO) algorithm. Additionally, the paper discusses the importance of adaptive controllers in addressing issues associated with incorrect PID controller selection and highlights the benefits of using the FA-GA in energy optimization and comfort improvement. Overall, the proposed model offers an effective solution for efficient energy consumption optimization and enhanced user comfort in diverse settings through the integration of advanced algorithms and optimization modules.

This article presents an experimental study focused on the impact of supplementing pure gasoline (E0) with bioethanol, gradually increasing the biofuel concentration up to 70% (E10, E50, and E70). The research was conducted in two phases: In the first phase (Part I), the engine's operation involved varying engine speeds (n = 2000 rpm, n = 2500 rpm) and adjusting throttle openings (15%, 20%, 25%) to analyze changes in brake torque, thermal efficiency, and ecological indicators. The second phase (Part II) aimed to complement and clarify the study data. Here, the engine was maintained at a constant speed (n = 2000 rpm) and brake torque (MB = 80 Nm) while altering ignition timing. The findings revealed that increasing the bioethanol concentration up to 70% led to modest enhancements in engine brake torque and thermal efficiency. However, the most significant impact was observed in the reduction of greenhouse gas emissions and incomplete combustion byproducts. The study also established that achieving higher thermal efficiency requires compensating for the extended ignition delay phase resulting from bioethanol addition by advancing ignition timing. Nevertheless, this approach is constrained by the escalating emissions of carbon dioxide and hydrocarbons. These findings provide valuable insights into optimizing the balance between bioethanol supplementation, engine performance, and environmental sustainability in spark ignition engines.

This study delves into the dynamics of relational energy (RE) within organizational context, examining some of its antecedents and decedents. Specifically, it investigates the influence of psychological capital (PsyCap) and humor on RE, and subsequently, the latter’s impact on job performance (JB) mediated by job engagement (JE). A research model based on structural equation modelling carried out with 481 employees in private service industries demonstrates several key relationships. It reveals that both PsyCap and affiliative humor positively affect RE, while aggressive humor exerts a negative influence. Furthermore, RE shows positive association with JE and JP, with JE serving as a mediator. To the authors’ knowledge, this is the first study to present an integrated model encompassing this exact combination of influencers and consequences of RE as well as to be investigated within Western Balkans cultural context. Therefore, it represents a novel approach. Additionally, the research addresses crucial questions regarding the existence and strategic significance of RE within organizational interactions. The findings offer valuable insights for organizations seeking to enhance employee engagement, performance, and wellbeing – even during health crises such as COVID-19 – by fostering RE. The study advances the understanding of RE in organizational settings and provides a foundation for future research in this domain.

The need to address climate change and establish sustainable urban environments has driven increased efforts in Europe to develop climate-neutral cities. This study highlights the importance of integrating solar energy technologies and nature-based solutions as key strategies to achieve climate neutrality. By examining current practices, emerging trends, and case examples, it explores the benefits, challenges, and prospects associated with the integration of solar energy and nature-based solutions in urban contexts. The study presents a pioneering approach to assess the urban heat and climate change mitigation benefits of combining building-integrated photovoltaics and nature-based solutions specifically within the European context. The results emphasize the synergistic relationship between nature-based components and solar conversion technology, identifying effective combinations for different climatic zones. In warmer regions of Southern Europe, strategies like rooftop photovoltaics on cool roofs, photovoltaics shadings, green walls, and urban trees have demonstrated effectiveness. Conversely, mid- and high-latitude European cities have seen positive impacts through the integration of rooftop photovoltaics and photovoltaics facades with green roofs and green spaces. As solar cell conversion efficiency improves, the environmental impact of photovoltaics is expected to decrease, facilitating their integration into urban environments. The study emphasizes the importance of incorporating water bodies, cool pavements, spaces with high sky-view factors, and effective planning in urban design to maximize resilience benefits. It also highlights the significance of prioritizing mitigation actions in low-income regions and engaging citizens in the development of social photovoltaics positive energy houses, resilient neighbourhoods, and green spaces. By adopting these recommendations, European cities can lead the way in creating climate-neutral urban environments that prioritize clean energy, nature-based solutions, and the overall well-being of residents. The findings underscore the need for a multidisciplinary approach that combines technological innovation, urban planning strategies, and policy frameworks to effectively achieve climate neutrality in European cities.

The thermal insulation properties of building walls are critical to the overall energy efficiency and comfort of a building. One important factor that can affect these properties is the type of bricks used in construction. Bricks can vary in their geometry and thermal coefficient, which can impact their ability to transfer heat through the wall. The geometry of a brick can affect its thermal properties by altering the amount of air trapped within it and the surface area available for heat transfer. Hollow bricks or those with complex geometries may have lower thermal conductivity than regular solid bricks due to the air pockets trapped within them. Conversely, larger surface areas on the exterior of the brick can increase heat transfer. The thermal coefficient of clay, a common material used in brick production, is another important factor. Clay has a relatively low thermal conductivity, meaning it is a poor conductor of heat. However, the quality of the clay, as well as the firing temperature and duration used in brick production, can impact its thermal coefficient. Higher firing temperatures and longer firing times can result in a more compact and dense clay brick, which can improve its thermal properties. In summary, the thermal insulation properties of building walls can be significantly affected by the type of bricks used in their construction. It is important to consider the geometry and thermal coefficient of the bricks when designing a building to achieve the desired level of thermal insulation. By selecting bricks with appropriate properties, designers can help to improve the energy efficiency and comfort of the building while reducing its environmental impact.

The sustainable management of Land - Water - Energy - Food (LWEF) nexus requires an envi-ronmental characterization that allows the comparison of complex interlinkages between nexus resources and livelihoods. This complexity makes this characterization difficult coupled with limited study in quantifying sustainability of LWEF nexus and its linkage with livelihood. Therefore, the present study aimed to investigate the link between sustainable LWEF nexus and livelihoods. We used analytical hierarchy process and pairwise comparison matrix in combina-tion with weighting model. The result of composite LWEF nexus index was 0.083 representing, low sustainability. This could be linked with nexus resources consumption, use, and manage-ment. From the analysis of the weight of land, water, energy and food nexus resources, the highest weight was observed for food. The focus of on food production only shows no clear synergy on provisioning, supporting or regulating nexus resources to address livelihoods. The result further showed that LWEF nexus resources have strong correlation with livelihoods. This was evidenced by social (r>0.8, P<0.01), natural (r>0.3, P<0.05) and physical (r>0.6, P<0.01) liveli-hood indicators showed strong positive correlation with LWEF nexus resources. From this re-sults, it was observed that managing nexus resources not only provide a significant contribution to achieve sustainable LWEF nexus, but also be effective for enhancing livelihood through food security. This could be attained by strong evidence based policy to ensure sustainable use of nexus resources. The results provided by this study would serve as the foundation for future study, policy formulation and implementation.

Drone technology has undoubtedly become an integral part of our everyday life these days. The business and industrial use of unmanned aerial vehicles (UAV) can provide advantageous solutions in many areas of life, and they are also optimal for emergency situations and for accessing hard-to-reach places. However, their application poses numerous technological and regulatory challenges to be overcome. One of the weak links in the operation of UAVs is the limited availability of energy. In order to address this issue authors developed a novel trajectory planning method for UAVs to optimize the energy necessity during flight. First, an “energy map” was created, which was the basis for trajectory planning, i.e., determining the energy consumption of the individual components. This was followed by configuring the 3D environment including partitioning of the work space (WS), in fact, defining the free spaces, occupied spaces (obstacles) and semi-occupied/free spaces. Then the corresponding graph-like path(s) were generated on the basis of the partitioned space, where a graph search-based heuristic trajectory planning was initiated, taking into account the most important wind conditions including velocity and direction. Finally, in order to test the theoretical results, some sample environments were created to test and analyse the proposed path generations. The method eventually proposed was able to determine the optimal path in terms of energy consumption.

The study reveals correlations between the parameters of ions and their HOMO and LUMO orbital energy level values. In particular, it demonstrates a clear correlation for the ion adsorption parameters on model electrodes: the aluminum oxide (0001) surface, graphene and Au (111) surface. Correlations are also observed for the parameters of ion binding to water and dimethyl carbonate molecules, which are often used as solvents. In addition, the dipole moment, polarizability and solvation energy of ions are well correlated with the values of the molecular orbital energies, and for anions a dependence on the oxidation potential is observed. The obtained descriptors make it possible to select ions with desired values for a specific problem. As an illustrative example, in this work we consider the problem of displacement of water molecules from the inner electric double layer by ions, which is one of the factors increasing the potential window in electrolytes of aqueous batteries. This approach can be applied in the rapidly developing field of aqueous electrolytes for battery or supercapacitor design, catalysis control through surface composition variations, as well as in studies of heavy metal ion binding to sorption materials.

Ecological Society is based on socioeconomic systems directed to the equilibrium of inter-relationships between environment, climate, production systems, technologies and human communities to promote the overall well-being of people and the Earth planet. It has a main goal for supporting sustainable development and equitable societies and achieving optimal health outcomes recognizing the interconnection between people, technologies, animals, plants, and their shared environment for the one health. Using data of scientific publications and patents until the year 2024, this study shows new technologies that can support the energy transition with the shift from fossil fuels to renewable energy sources in an effort to reduce CO₂ emissions for an ecological society having, whenever possible, zero-carbon economies to reduce environmental pollution and climate change and foster health and wellbeing of people. Results reveal that sustainable technologies supporting the transformation of the energy sector, economies and societies, and having a rapid growth, are blue hydrogen, floating photovoltaic systems, carbon capture and utilization, green hydrogen and liquid metal batteries. These findings can guide decisions of policymakers and stakeholders towards fruitful investments driving the transition from fossil-based to zero-carbon socioeconomic systems to have a long-run sustainable development of overall world system that has to direct towards an ecological society associated with one health.

This scientific article outlines the Artificial Intelligence Integrated Energy Education Framework (AI-IEEF), a transformative model designed to revolutionize energy education and management practices. The framework is organized into five distinct layers: Organizational (AI-enhanced administration systems), Financial (dynamic AI financial models), Technology (advanced simulation and modeling), Methodology (AI in curriculum development and personalized learning), and Social (AI for community engagement and impact). An expert panel used the fuzzy Delphi method to achieve consensus on twenty key factors within these layers, establishing a solid foundation for analysis. Following this, the Fuzzy Analytic Hierarchy Process (AHP) was employed to calculate precise weights for each layer and their respective factors, providing a quantitative assessment of their relative importance. These weight calculations are crucial, as they guide resource allocation and strategic decision-making to ensure the framework is optimized for the evolving needs of energy management. Furthermore, the article introduces five tailored variants of the AI-IEEF, each addressing specific aspects of energy education and offering a comprehensive approach to navigating the challenges in the field. The five variants include the Smart Campus Energy Education, Global Energy Policy Analysis, Renewable Energy Research and Development, Energy Workforce Development, and Community Engagement and Outreach variants. Each provides a distinct approach to energy education, from transforming campuses into living labs for hands-on learning to fostering international collaborations that explore the global implications of energy policy. These variants emphasize practical skills, policy analysis, and community-focused solutions, ensuring that students are well-prepared to contribute effectively to the energy sector.

A selective permeable membrane between two different solutions can generate osmotic pressure, Donnan potential, and ion/pH gradients based on various factors such as membrane type, solute concentration and temperature. In this study, we introduce a novel method for extracting energy from ion gradients through an innovative cycle, presenting intriguing experimental findings. Additionally, by leveraging Raoult’s Law, which describes the relationship between vapor pressure and solute presence, in conjunction with osmosis within a closed system, we successfully engineer the simplest iteration of Maxwell’s demon device. This pioneering approach to sustainable energy generation harnesses ambient temperature marking a significant advancement in energy research. Finally this renewable energy source is available all the time and everywhere.

The paper proposes a methodological way to compensate the imbalance between energy generation and consumption using the battery block of electric vehicles as energy reservoir through the well-known Vehicle to Grid system (V2G). The method is based on a simulation process developed by the authors that take into consideration the daily fluctuations of energy consumption as well as the power level generated by an energy source, either conventional, renewable or hybrid. The study shows that for very large electric vehicle fleet the system renders non-viable, since the remaining energy in the battery block to let the electric vehicle usable for running during daytime avoids to compensating for the energy grid imbalance, only allowing to cover a percentage of the energy imbalance, which the proposed methodology may optimize. The analysis of the proposed methodology also shows the viability of the system when being applied to a small fleet of electric vehicles, not only compensating for the energy imbalance but also preserving the required energy in the battery of the electric vehicle to make it run. The method allows predicting the optimum size of electric vehicle battery, which depends on the energy generation level, coverage factor of the energy imbalance and size of the electric vehicle fleet.

In thermodynamic theory, free energy (i.e., available energy) is the concept facilitating the combined applications of the theory’s two fundamental laws, the first and the second laws of thermodynamics. The critical step was taken by Kelvin, then by Helmholtz and Gibbs— that in natural processes, free energy dissipates spontaneously. With the formulation of the second law of entropy growth, this may be referred to as the dissymmetry proposition manifested in the spontaneous increase of system/environment-entropy towards equilibrium. Because of Kelvin’s pre-entropy-law formulation of free energy, our concept of free energy is still defined, energy-centrally, as body’s internal energy or enthalpy, subtracted by energy that is not available within a framework on the premise of primacy of energy, in which free energy dissipates spontaneously and universally. This primacy of energy is called into question because the driving force to cause a system’s change is the purview of the second law. This paper makes a case for an engineering thermodynamics framework, instead, to be based on the premise of the primacy of dissymmetry over free energy. With Gibbsian thermodynamics undergirded with dissymmetry proposition and engineering thermodynamics with the dissymmetry premise, the two branches of thermodynamics are unified to become classical thermodynamics.

This study advances the field of solar irradiance nowcasting by introducing a discrete-level classification approach, diverging from traditional continuous measurement methods. Grounded in a need for cost-effective and modular solutions, the research employs high-resolution computer vision coupled with a deep learning framework to predict Direct Normal Irradiance (DNI). By harnessing the capabilities of a Logitech C900 1080p HD camera and an NVIDIA Jetson module, the study achieves real-time data processing, pivotal for CSP systems' operational efficiency. The core of the methodology is the ResNet-50 convolutional neural network, refined via transfer learning on a bespoke dataset, culminating in a predictive accuracy of 85.78%. This discrete classification model contrasts with conventional, costly instruments like the MS-57, offering a novel and accessible alternative for DNI estimation. Such innovation not only demonstrates high predictive accuracy but also signifies a shift towards less resource-intensive and more adaptable solar energy forecasting tools, contributing a significant leap towards optimizing renewable energy systems.

The urgency for a shift towards cleaner and more efficient energy alternatives for power generation is underscored by the escalating demand for energy and the detrimental environmental impacts of conventional fossil fuels. In the case of automotive power, electric vehicles are being adopted in many applications, however, challenges remain such as extended charging periods and limited ranges between charges. Therefore, this research study conducts a techno-economic analysis of renewable energy technologies (including solar modules, wind turbines and piezoelectric materials) to augment the efficiency and sustainability of electric buses. The study examines the scope for these technologies to be adopted on double-decker electric buses in London in the United Kingdom. The solar modules are placed on the rooftop and sides of the bus generating 15.9 kWh/day and the wind turbine in the front bumper of the bus generates 8.3 kWh/day. However, the piezoelectric material generated only 22.6 Wh/day, rendering it an impractical inclusion in further analysis. Therefore, both the solar modules and wind turbines combined generate 24.2 kWh/day, which can increase the driving range by 16.3 km per day and this results in savings of 19.36 minutes for charging at the stations. Investing in such projects would have a positive return as the internal rate of return (IRR) and net present value (NPV) are 2.8% and £11,175 respectively. The annual revenue would be £6,712, and the greenhouse gas (GHG) reduction would be two metric tons annually. Electricity exported to the grid, the electricity export rate, and the initial investment are identified as key factors influencing power outage in a sensitivity analysis. In conclusion, this numerical modelling study paves the way for experimental validation towards implementation of renewable energy technologies on electric bus fleets.

This work explores five falling film evaporator (FFE) simulation approaches combined with energy consumption minimization strategies, namely Mechanical Vapor Recompression and Thermal Vapor Recompression (MVR and TVR respectively). Global system analysis and advanced dynamic optimization strategies are then investigated to minimize steam consumption, the cost of steam, the total annualized cost and maximizing product yield. The results indicate that a higher TVR discharge pressure, or MVR compression ratios, along with higher feed temperatures enhance evaporation with but increase operational costs. The most economic option includes three evaporator effects with TVR for achieving 50% product dry mass content. However, for a 35% dry mass content, MVR becomes cost-effective with an 11% reduction in unit electricity prices or a simultaneous 7% drop in electricity prices and a 5% increase in gas-based steam prices. Furthermore, switching from milk powder production to milk concentrates, an annual cost reduction ranging from 10.75 to 44% is achieved. Also, a forecasted 20% (or more) reduction of biomass-based steam cost can lead to lower annual expenditure comparing with the nominal NG-based steam Case. Regarding the total annualized cost, for a new plant design, optimization strategies lead to a 9 - 45% reduction in the total cost depending on the Case under consideration.

New ways of generating energy are currently being discussed, with a transition from traditional primary sources to more environmentally friendly options, particularly renewables. Energy storage is also closely related to this transition. Battery storage currently dominates this area. However, flywheel energy storage system (FESS) technology offers an alternative that uses stored kinetic energy to be transformed into mechanical energy and, using a motor-generator, electrical energy. FESS technology is thus flexible and can be applied in different industrial applications. The management of the technology of recycling W-MMC waste material from other products and the subsequent trial production of high-strength W-MMC material with a density of more than 17 500 kg/m3 from recycled powders allowed to test the limits of the so-called "heavy" flywheels used in rotor production. Materials with densities ≥ 7 800 kg/m3, and operating at lower to medium speeds up to 20 000 rpm. The results achieved lead to the conclusion that the developed recycled materials of the W-MMC type with a density ≥ 17 500 kg/m3, with a yield strength of 1 200 - 1 700 MPa depending on the production method, can be used as a substitute for the structural steels used today, without an enforced reduction of the maximum allowed rotor speed due to exceeding the maximum allowed stress.

In physics, thought experiments are impressive heuristic tools. They are valuable instruments to help scientists find new results and to teach students the known ones. However, as we shall show, they should always be received with prudence, even when they are a shortcut to 'prove' well-established results. Here, we show that the most widely known thought experiments devised to derive the gravitational frequency shift from energy conservation are, in fact, problematic. When properly set and correctly read, those thought experiments reveal that the existence of the gravitational frequency shift is, in fact, at odds with energy conservation. We also propose two new simple thought experiments, one using the conservation of energy and the other the conservation of linear momentum, that corroborate that conclusion, showing that those conservation principles do not imply the gravitational frequency shift. We think that our results may be of some epistemological interest and could serve as a warning sign on how thought experiments should be received and trusted.

The IPCC’s sixth assessment report projects 15% to 43% (44 EJ/y – 310 EJ/y) of global primary energy to be generated by biomass in 2050 across multiple GHG mitigation scenarios. That report also emphasises the importance of electrification to meet GHG reduction targets. With increased reliance on electric power, and increased appeal to biomass, bioenergy for electricity is expected to play a major role in future energy markets. What makes the bioenergy solution more attractive is its reported reasonable Energy Return on Investment (EROI). However, generation at large scale is projected to be greatly dependent on crops and plantations. This shifts the GHG emissions concern to be concerns over land use and other emissions integrated in the bioenergy lifecycle. It is therefore vital to know whether the potential of electricity generation from biomass outweighs environmental impact of bioenergy. This paper evaluates the potential of biomass electricity mainly generated from short rotation woody crops combustion in generating green energy. This is done using the “Green EROI (EROIg)” quantification methodology, which indicates the net energy generated to society after investing in ecosystem maintenance energy (ESME). ESME is a non-monetary weighting mechanism of an entity’s different lifecycle environmental impacts. This study found that the EROIg of bioelectricity is marginally larger than unity when converted to its primary equivalent form (EROIg-PE) which indicates that the technology is somewhat energetically viable if its production was to be green. Three design options were proposed to improve bioenergy’s EROIg performance, these include adding 20% waste wood in the combustion mix, staggered harvesting and plantation to achieve annual harvest and pelletizing wood. This approach appeared to improve the EROIg especially for pelletizing, due to its simultaneous reduction in storage and transport costs, making the production energetically and environmentally viable even at a 1 : 1 secondary : primary ratio with an EROIg of 1.11 and an EROIg-PE of 3.17. We conclude with the discussion of the multiple indirect advantages of growing crops that can be used for energy generation, and a discussion on how this technique can be used alongside others to help them generate cleaner energy while facing the current global climate, biodiversity and waste issues.

This research examines the impact of social equity on energy consumption. We constructed a digital twin for residential energy consumption by enriching the synthetic population with real-world surveys and feeding them with other environmental and appliance data to the energy modeling framework. We analyzed household hourly energy consumption data from Albemarle County and Charlottesville City in Virginia, USA, for the year 2019. We used clustering analysis to identify patterns in social equity and energy consumption. The results demonstrated the impact of different residential attributes on energy poverty. Statistical analyses, including ANOVA and Chi-Squared tests, were conducted to test for significant differences between racial groups in quantitative and categorical variables. The study found that race is significant in determining the location and quality of housing. People of color often live in areas with higher pollution and less access to green spaces. Additionally, income levels and the age of the house are influential factors in determining energy efficiency. Future work should focus on collecting and analyzing data at the country level and using qualitative data collection methods to gain a more comprehensive understanding of social equity issues concerning energy consumption. Overall, this study provides valuable insights into the relationship between different residential attributes and energy consumption, which can inform policy development to promote more equitable and sustainable communities.

The dissolution of Al2O3 non-metallic inclusions from slag containing FexO was investigated in this study. The slag system used in the experiments was a quaternary system of CaO-SiO2-Al2O3-FexO. The composition of the slag was studied by fixing the basicity (CaO/SiO2 ratio) to 1 and varying the FexO content to 10 and 20wt%. In addition, the experimental temperature was varied as 1550℃, 1575℃, and 1600℃ to study the effect of temperature on the Al2O3 dissolution behavior. The experimental equipment is a single hot thermocouple apparatus. The dissolution rate of Al2O3 particles increased linearly with increasing temperature and FexO content. In addition, the mass transfer activation energy of Al2O3 dissolution in FexO 10wt% and FexO 20wt% was calculated by an Arrhenius type analysis. The obtained mass transfer activation energies were 159 and 189 kJ/mole, respectively.

We investigated new anodic coloring materials that are used as ion storage layers in complementary energy storage electrochromic devices (ESECDs) to enhance their electrochromic storage performance. In this study, we fabricated counter electrodes (ion storage layers) using IrO2 doping NiO (Ir: NiO) film through cathodic arc plasma (CAP) with varying surface charge capacities. We investigated the influence of MoO3-doped WO3 (Mo: WO3) film by various Ar/O2 gas flow ratios (1/4, 1/5, and 1/6). The ESECDs used in the demonstration were 10×10 cm2 in size. They achieved optical transmittance modulation of Ir: NiO- ESECDs (glass/ITO/ Mo: WO3/gel-polymer electrolytes/ Ir: NiO /ITO/glass), ΔT=53.3% (from Tbleaching (66.6%) to Tcoloration (13.1%)). The ESECDs had a quick coloration time of 3.58 seconds, a rapid bleaching time of 1.24 seconds, and high cycling durability. It remained at 45% transmittance modulation even after 3000 cycles. New anodic materials can provide an alternative to traditional active materials for bi-functional electrochromic batteries.

Energy efficiency is, in principle, a simple idea: an output of human value, for example, vehicle-km traveled, divided by the needed input energy. Efficiency improvements are regarded by many as an important means of mitigating not only climate change, but also other environmental problems. Accordingly, many countries have efficiency ratings for appliances and efficiency standards for road vehicles. Despite the vast number of articles published on energy efficiency, few question whether it is a useful or accurate measure in its present form. This review addresses this lack, by a critical review of the literature, not only in energy efficiency, but in other areas of research, such as ‘energy services’, that can help broaden the scope of this idea, both geographically and conceptually. These shortcomings are illustrated in case studies of road passenger transport and buildings. The main findings are that energy efficiency inevitably has an ethical dimension, that feedbacks are more widespread than generally considered, and that conventional efficiency measures omit important energy input items, particularly those concerned with mining of the materials needed for renewable energy plants. Finally, the key results of this review are summarized, and its limitations are discussed, as is the future research needed to overcome these shortcomings.

This paper presents the goals and components of a quantitative energy balance assessment framework to define PEDs flexibly in three important contexts: the context of the district's density and RES potential, the context of a district's location, induced mobility and the context of the dis-trict's future environment and its decarbonized energy demand or supply. It starts by introducing the practical goals of this definition approach: achievable, yet sufficiently ambitious to be inline with Paris 2050 for most urban and rural Austrian district typologies. It goes on to identify the main design parts of the definition: system boundaries, balancing weights and balance targets and argue how they can be linked to the definition goals in detail. In particular we specify three levels of system boundaries and argue their individual necessity: operation, including everyday mobili-ty, including embodied energy and emissions. It argues that all three pillars of PEDs, energy effi-ciency, onsite renewables and energy flexibility can be assessed with the single metric of a prima-ry energy balance when using carefully designed, time-dependent conversion factors. Finally, it is discussed how balance targets can be interpreted as information and requirements from the sur-rounding energy system, which we identify as a "context factor". Three examples of such context factors, each corresponding to the balance target of one of the previously defined system bounda-ries operation, mobility and embodied emissions are presented: Density (as a context of opera-tion), sectoral energy balances and location (as a context for mobility) and an outlook of a person-al emission budgets (as a context for embodied emissions). Finally, the proposed definition framework is applied to seven distinct district typologies in Austria and discussed in terms of its design goals.

From the standpoint of Neoliberal Institutionalism, this study explores Malaysia's participation in activities that make energy the topic and/or object of foreign policies, whether through bilateral or multilateral engagements. This research, which aims to evaluate the relevance of energy in Malaysia's economy and diplomacy and to explain Malaysia's reason for its involvement in these cooperations, is necessary because of Malaysia's growing involvement in the global energy market. Information for this study was gathered from a variety of government sources, interviews, published statistical data, and previous studies. The study demonstrates how vital energy is to Malaysia's economy. The Lao PDR-Thailand-Malaysia-Singapore Power Integration Project (LTMS-PIP) initiative, in which Malaysia is participating, is evidence of the viability of multilateral power commerce in the area. The Peninsula Gas Utilisation (PGU) pipeline in Peninsular Malaysia and the Four-Fuel Diversification Policy 1981 (4FDP 1981), which increases natural gas utilisation, are related to Malaysia's participation in the Malaysia-Thailand Joint Development Area (MT-JDA). Malaysia would want to think about streamlining its energy administration.

A Shape Memory Alloy (SMA) enabled Overtopping Wave Energy Converter (OWEC) that maximizes its overtopping discharge, and thus energy output under different wave conditions is presented. Among all the parameters affecting the overtopping discharge rate, the crest freeboard height is the most influential one to control the overtopping discharge rate and the stored overtopping volume behind it. Currently, all the OWEC crest freeboard heights are fixed by design to maximize the discharge rate on one particular sea state. In the present study, we show that the SMA can adjust the crest freeboard height through a control system based on the sea state and achieve an optimal overtopping discharge rate. A scaled OWEC model is built in the lab with its crest freeboard height controlled by springs made of SMA. The length (and thus tension) of the springs is controlled by temperature changes by changing the passing current through the springs. By adjusting the length of the springs based on the incoming wave condition, we adjust the freeboard to an optimal height known to generate a maximum overtopping discharge rate for energy conversion. This smart material-enabled design can maximize the overtopping discharge and thus the output power of the OWEC under various wave conditions. Furthermore, the simplicity of using SMA springs as the actuator leads to the minimum number of moving mechanical parts, which can remarkably decrease maintenance costs. As the proof of concept, two types of tests are conducted in the laboratory using the same OWEC model under several random wave trains generated from spectra with different significant wave heights - one type with a fixed crest freeboard height and the other type featuring the adjustable crest freeboard height controlled by the springs. The substantial increase of harvested output power in the OWEC with the adjustable crest freeboard height may pave the way for more efficient wave energy conversion systems.

Although the fusion energy sector is at a nascent stage, the private fusion energy market has grown. There are currently 38 private fusion energy companies around the world aiming to commercialise fusion energy in early 2030s and 2040s. Given the capability of fusion energy in transforming today’s energy paradigm and the global character of the market, it is important to analyse how these companies are interacting with international human rights standards. Therefore, this work investigates the involvement of the private fusion energy sector with two voluntary international initiatives in particular: the UN Global Compact and the UN Guiding Principles on Business and Human Rights (UNGP). This study attempts to answer two research questions: (i) Are private fusion energy companies participating in the UN Global Compact? (ii) How are private fusion energy companies publicly implementing the UNGP? Content analysis of secondary data collected from the UN Global Compact, Fusion Industry Association, ITER and companies’ official website as well as published reports is adopted. In summary, this work finds that private fusion energy companies are neither participants nor signatories of the UN Global Compact. Their observance of the UNGP is also very poor. This study contributes to the field by highlighting this gap which the private fusion energy companies need to consider and take measures in order to create a salutary human rights sector.

Like living organisms, cancer cells require energy to survive and interact with their environment. Recently, investigators demonstrated that cancer cells can hijack mitochondria from immune cells. This behavior sheds light on a pivotal piece in the puzzle of cancer, the ‘dependence’. This article illustrates how new, functional mitochondria help cancer cells to survive in the harsh tumor microenvironment, evade immune cells, and improve their malignancy. Finally, we will discuss how blocking the routes supplying energy for cancer cells can improve the treatment outcomes of radiotherapy, chemotherapy, and immunotherapy. This article provides a new theory in oncology, the ‘energy battle’ between cancer and immune cells. It alludes each party with a higher energy level can be the winner. This theory explains cancer biogenesis and provides novel insights to improve treatment outcomes.

Airborne wind energy (AWE) systems use tethered flying devices to harvest higher-altitude winds to produce electricity. For a successful deployment of these systems, it is crucial to understand how the public perceives them. If public concerns about the technology are not taken seriously, implementation could be delayed or, in some cases, prevented, resulting in increased costs for project developers and a lower contribution of the sector to renewable energy targets. This literature review assessed the current state of knowledge on public responses to AWE. An exhaustive literature search led to the identification of 40 relevant publications that were reviewed. The literature assumed that the safety, visibility, acoustic emissions, ecological impacts, and the siting of AWE systems shape public responses to the technology. The reviewed literature views people’s responses to AWE very optimistically but lacks scientific evidence to back up its claims. It seems to overlook that the influence of AWE’s characteristics (e.g., visibility) on public responses will also depend on a range of situational and psychological factors (e.g., people’s general attitude towards AWE, the public’s trust in project developers). Therefore, empirical social scientific research is needed to increase the field’s understanding of public responses to AWE and thereby facilitate deployment.

As a consequence of the increasing share of renewable energies and sector coupling technologies, new approaches are needed for the study, planning, and control of modern energy systems. Such new structures may add extra stress to the electric grid, as is the case with heat pumps and electrical vehicles. Therefore, the optimal performance of the system must be estimated considering the constraints imposed by the different sectors. In this research, a dispatch optimization method with an iterative grid constraint generation, decoupled from the linear unit commitment problem, is employed. From the considered scenarios, it was found that in a typical German neighborhood with 150 households, PV penetration of ∼5kWp per household can lead to curtailment of ∼60MWh per year due to line loading. Furthermore, the proposed method eliminates grid violations due to the addition of new sectors reducing the curtailment up to 60%. With the optimization of the heat pump operation, an increase of 7% of the self-consumption was achieved with similar results for the combination of battery systems and electrical vehicles. In conclusion, a safer and optimal operation of a complex energy system is fulfilled. Safer control strategies and more accurate plant sizing could be derived from this work.

In this work, an energy-saving smart light controlling system has been proposed that can main-tain the desired intensity of light in a room automatically. Unlike the conventional light control system, the proposed system splits a large room into several zones and analyzes the light inten-sity of each zone; hence, the controlling unit adjusts the light intensity to the desired level. The main controlling unit consists of a light sensor, a motion sensor, a relay with a driver unit, an LCD display, etc. for controlling light efficiently to reduce the power waste. The sensors meas-ure the intensity of light, based on the standard light intensity data chart the controller units make a decision how many light bulbs are needed to be switched ON/OFF in a particular zone. Moreover, the system automatically switched-OFF all light bulbs when there is nobody in the room. Proteus design suite 8.0 is used to design and simulation of the proposed system. Moreo-ver, the PCB layout is designed using ExpressPCB version 7.5.0. The proposed system is capable of minimizing the power loss by up to 44% in comparison to the conventional light manage-ment system.

Integration of battery energy storage in photovoltaic (PV) systems can reduce the electricity costs and provide desirable flexibility and reliability to these systems decreasing renewable energy fluctuations. This paper presents a review of the PV-battery application in Brazil, highlighting the challenges and prospects based on the state-of-art. A PV-battery systems description is presented in this work, as well as the most applied battery technology and its comparison. The paper also describes the set of applications such as voltage and frequency regulation, renewable energy integration, power quality, etc. In the Brazilian scenario, there are applications of PV-battery systems, most of them part of research and development projects (R&amp;D’s), and some real cases are shown, including its goals, applied equipment, operation modes, strategies, and perspectives. Additionally, this work evaluates the Brazilian scenario regarding the energy storage systems implementation challenges, such as regulatory barriers, business models, and opportunities for R&amp;D in the energy market. In conclusion, it is need develop proper regulatory models to expand PV-battery systems and make them visible to the agents in the electricity sector.

The generalized dual-kinetic-balance approach for axially symmetric systems is employed to solve the two-center Dirac problem. The spectra of one-electron homonuclear quasimolecules are calculated and compared with the previous calculations. The analysis of the monopole approximation with two different choices of the origin is performed. Special attention is paid to the lead and xenon dimers, Pb82+–Pb82+–e− and Xe54+–Xe54+–e−, where the energies of the ground and several excited σ-states are presented in the wide range of internuclear distances. The developed method provides the quasicomplete finite basis set and allows for construction of the perturbation theory, including within the bound-state QED.

In this paper we re-investigated the relationship between the symmetry of inertial systems and the Lorentz transformation. We found that when we just follow the following three principles: (1)we can define the time in the whole space with a prescribed clock synchronization, (2)the time-space is uniform and the space is isotropic and (3)all the inertial systems are equivalent, then we can totally construct a general coordinate transformation to meet the symmetry of inertial systems, and with a special assumption on the speed of light, we can construct a non-Lorentz transformation between inertial systems to make the particle’s energy have a limited value, which is similar to the rainbow model. Similar to the usual Lorentz violating models, the non-Lorentz transformation in this paper lead to a new modified disperse relation. We applied the obtained disperse relation to analyze the photon’s arrival time lag effect in astronomy and found that the "maximum energy" derived in our model is somewhat related to the "maximum energy" assumed in the rainbow model.

IoT system becomes hot topic nowadays for smart home, IoT helps devices to communicate together without human intervention inside home, so it is offering many challenges. A new smart home IoT platform powered using electromagnetic energy harvesting is proposed in this paper. It contains a high gain transmitted antenna array and efficient circular polarized array rectenna system to harvest enough power from any direction to increase life time of the batteries used in IoT system. Optimized energy consumption, the software with adopting the Zigbee protocol of the sensor node and low power microcontroller are used to operate in lower power modes. The proposed system has an 84.6 days lifetime which is approximately 10 times the lifetime for similar system. On the other hand, the proposed power management circuit operated at 0.3 V DC to boost the voltage to ~3.7V from radio frequency energy harvesting and manage battery level to increase the batteries lifetime. A predictive indoor environment monitoring system is designed based on a novel hybrid system to provide a non-static plan, approve energy consumption and avoiding failure of sensor nodes in smart home.

This article presents a method of segmenting images with gray levels that uses Onicescu's information energy calculated in the context of the neutrosophic theory. Starting from the information energy calculation for complete neutrosophic information, it is shown how to extend its calculation for incomplete and inconsistent neutrosophic information. The segmentation method is based on calculation of thresholds for separating the gray levels using the local maximum points of the Onicescu information energy.

In recent decades, power consumption has become an essential factor in attracting the attention of integrated circuit (IC) designers. Multiple-valued logic (MVL) and approximate computing are some techniques that could be applied to integrated circuits to make power-efficient systems. By utilizing MVL-based circuits instead of binary logic, the information conveyed by digital signals increases, and this reduces the required interconnections and power consumption. On the other hand, approximate computing is a class of arithmetic computing used in systems where the accuracy of the computation can be traded-off for lower energy consumption. In this paper, we propose novel designs for exact and inexact ternary multipliers based on carbon-nanotube field-effect transistors (CNFETs). The unique characteristics of CNFETs make them a desirable alternative to MOSFETs. The simulations are conducted using Synopsys HSPICE. The proposed design is compared against existing ternary multipliers. The results show that the proposed exact multiplier reduces energy consumption by up to 6X. At the same time, the best inexact design improves energy efficiency by up to 35X compared to the latest state-of-the-art methods. Using the imprecise multipliers for image processing provides evidence that these proposed designs are a low-power system with an acceptable error.

Environmental and economic needs drive the increased penetration of intermittent renewable energy in electricity grids, enhancing uncertainty in market conditions prediction and network constraints. Thereafter, the importance of energy systems with flexible dispatch is reinforced, ensuring energy storage as an essential asset for these systems to be able to balance production and demand. In order to do so, such systems should participate in whole-sale energy markets, enabling competition among all players, including conventional power plants. Consequently, an effective dispatch schedule considering market and resource uncertainties is crucial. In this context, an innovative dispatch optimization strategy for schedule planning of renewable systems with storage is presented. Based on an optimization algorithm combined with a machine learning approach, the proposed method develops a financial optimum schedule with the incorporation of uncertainty information. Simulations performed with a concentrated solar power plant model following the proposed optimization strategy demonstrate promising financial improvement with a dynamic and intuitive dispatch planning method, emphasizing the importance of uncertainty treatment on the enhanced quality of renewable systems scheduling.

This paper presents a comparison between a kite model with a constant-length tether and a model based on a system identification algorithm. The concept of system identification is applied to predict the uncertainties related to the variation of the wind speed and the shape deformation of the tethered membrane wing during flight. A pole-placement controller is used to ensure that the kite follows the planned flight path. Thus, we can determine the required locations of the closed loop poles, and then enforce them by changing the controller's gains in real-time. The capability of the system identification algorithm to recognize sudden changes in the dynamic model, and the ability of the controller to stabilize the system in the presence of such changes are confirmed. Furthermore, the system identification algorithm is applied to determine the parameters of a kite with variable-length tether used in a flight test of the 20 kW kite power system of TU Delft. Experimental data of this test were compared with the system identification results in real-time and significant changes were observed in the parameters of the dynamic model which heavily affect the resulting response.

A solution of general relativity is presented that describes an Alcubierre propulsion system in which it is possible to travel at superluminal speed while reducing the energy, by an arbitrary value.

This paper proposes a method of extracting energy from zero-point energy and evaluates the amount of energy gained. In addition, this electric circuit-based approach exhibits the Meissner effect, suggesting a new type of superconductivity that does not require refrigeration. The proposed method can provide extremely large amounts of energy, which is more than a conventional power station, without consuming fossil fuels or emitting radiation. Thus, it has the potential to solve the global energy problem. It involves preparing two electric loops containing diodes and connecting the loops together with current sources. The diodes are oriented in the same direction within each loop but in opposite directions in different loops. With this setup, the currents from the current sources build iteratively within the loops, resulting in large output currents. Our numerical analysis indicates that extremely large electric potentials are produced, which in turn yield large output currents. In addition, we confirm numerically that the voltage is zero around a loop and show analytically that the Meissner effect is present, proving the existence of a new type of superconductivity. Furthermore, when we introduce induction coils to not break the loop’s symmetry, they store extremely large amounts of energy and we can thus obtain energy from them via discharge currents.

Power disaggregation aims at determining the appliance-by-appliance electricity consumption leveraging upon a single meter only, which measures the entire power demand. Data-driven procedures based on Factorial Hidden Markov Models have been proven remarkable results on energy disaggregation. Nevertheless, those procedures have various weaknesses: there is a scalability problem as the number of devices to observe raises and the algorithmic complexity of the inference step is severe. DNN architectures, such as Convolutional Neural Networks, have demonstrated to be a viable solution to deal with FHMMs shortcomings. Nonetheless, there are two significant limitations: a complicated and time-consuming training system based on back-propagation has to be employed to estimates the neural architecture parameters, and large amounts of training data covering as many operation conditions as possible need to be collected to attain top performances. In this work, we aim to overcome those limitations by leveraging upon the unique and useful characteristics of the extreme learning machine technique, which is based on a collection of randomly chosen hidden units and analytically defined output weights. Experiment evaluation has been conducted using the UK-DALE corpus. We find that the suggested approach achieves similar performances to recently proposed ANN-based methods and outperforms FHMMs. Besides, our solution generalises well to unseen houses.

This article makes a general analysis of the supply chain of photovoltaic systems in Colombia, taking as a starting point a conceptual base and the current situation of the country in this sector. This article especially will contemplate the non-interconnected areas (ZNI) to the electricity grid in the national, due to its complexity in the logistics issues. Likewise, the work performs a graphical representation of the stages and processes of the supply chain using a powerful-modeled tool such as the Petri Nets (PNs). Finally, it identifies some of the flaws in the operation and the joint of all the links of the logistic part and from there it is based the importance of the strategy of orientation to the supply chain (SCO) as a possible alternative to improve and to enhance the logistic processes of this type of systems.

1) Background: the budget of non-thermal energy in galaxy clusters is not well constrained, owing to the observational and theoretical difficulties in studying these diluted plasmas on large scales. 2) Method: we use recent cosmological simulations with complex physics in order to connect the emergence of non-thermal energy to the underlying evolution of gas and dark matter. 3) Results: the impact of non-thermal energy (e.g. cosmic rays, magnetic fields and turbulent motions) is found to increase in the outer region of galaxy clusters. Within numerical and theoretical uncertainties, turbulent motions dominate the budget of non-thermal energy in most of the cosmic volume. 4) Conclusion: assessing the distribution non-thermal energy in galaxy clusters is crucial to perform high-precision cosmology in the future. Constraining the level of non-thermal energy in cluster outskirts will improve our understanding of the acceleration of relativistic particles by cosmic shocks and of the origin of extragalactic magnetic fields.

The theory of limited numbers says that the number is not infinite, that is, the number is limited in parts or completely. To reach a conclusion about the limited number, one must understand the meaning of mathematics and varied spaces, therefore, one must understand that mathematics and spaces interact. Mathematics has the function of describing the world precisely, where numbers represent elements or facts that rationally belong to space, and spaces have different intensities of specific physical concepts in each space; therefore, there is no infinite element or fact due to differences in the intensities of specific physical concepts in spaces that do not allow for the fact or fact in all spaces.

In this paper, an extendable fuzzy robust speed controller suitable for induction motor drive system was proposed. Firstly, the two-degrees-of-freedom (2DOF) robust control technology with feedforward control and disturbance elimination method was adopted. Upon parameter variation and load disturbance, the motor drive system could utilize a robust controller to generate compensation signals and reduce the impact on controlling performance of the motor drive system. The magnitude of the compensation signal was adjusted via the weighting factor. However, should a fixed weighting factor be adopted, system instability might be generated easily when time delay and saturation of control force occur. Based on the above, the smart method of extendable fuzzy theory (EFT) was adopted in this paper to adjust adequate weighting factors, where the controlling performance of the induction motor drive system could be improved accordingly. The method divided the speed difference between motor speed command and actual speed of the induction motor, and the variation rate for such speed difference into 20 regional categories. The correlation degree between the speed difference of actual feedback, variation rate for speed difference and each regional category was then calculated, where more suitable weighting factor was selected. Therefore, the proposed extendable fuzzy robust 2DOF controller with variable weighting factor designed will allow better performance for response in speed tracking and load regulation. Lastly, the simulation software Matlab/Simulink was applied to simulate the utilization of the controlling method proposed for the induction motor drive system. For both the response in speed tracking and load regulation, the simulation results proved that the extendable fuzzy robust speed controller proposed provided better controlling performance than the conventional robust controller.

Across decades of contemporary discussion on sustainable development, a core debate has concerned the relationship between the economic, social, and environmental dimensions of sustainability. In recent years, a debate on economic growth versus degrowth has been going on discussing whether economic growth can be sustainable in environmental terms and whether economic degrowth can be sustainable in social terms. This conceptual and theoretical article has used the Sustainability Window, or ‘SuWi’ method, to theoretically determine the sustainable window of economies, as upper and lower bounds of future change in GDP, that could be deemed in line with environmental and social sustainability. All theoretically possible scenario paths of development are considered by combining the economic, environmental, and social dimensions, with the environmental and social productivities of GDP. In moving to sustainability analysis through SuWi it is noted that only four of the logically possible scenario paths could be considered theoretically 'sustainable’, and only if adhering to strict conditions. Two of the hypothesised scenarios involve economic growth and two of economic degrowth. The approach, including calculation formulas, has many potential uses in providing analysis and support to 21st century sustainability policymaking, including the United Nations Sustainable Development Goals.

The theory of heavy ion double charge exchange (DCE) reactions proceeding by effective rank–2 isotensor interactions is presented. Virtual pion–nucleon charge exchange interactions are investigated as the source for induced isotensor interactions, giving rise to the Majorana DCE (MDCE) reaction mechanism. MDCE is of a generic character, proceeding through pairs of complementary (π±,π∓) reactions in the projectile and target nucleus. The dynamics of the elementary processes is discussed where the excitation of pion–nucleon resonances are of central importance. Investigations of initial and final state ion–ion interactions show that these effects are acting as vertex renormalizations. In closure approximation, well justified by the finite pion mass, the second order transition matrix elements reduce to pion potentials and effective two–body isotensor DCE interactions, giving rise also to two–body correlations in either of the participating nuclei. Connections to neutrinoless Majorana double beta decay (MDBD) are elucidated at various levels of dynamics, from the underlying fundamental electro–weak and QCD scales to the physical scales of nuclear MDBD and MDCE physics. It is pointed out that heavy ion MDCE reactions may also proceed by competing electro–weak charge exchange processes, leading to lepton MDCE by electrons, positrons, and neutrinos.

My innovative entropy measure, Ismail entropy, namely, (IE) is an ultimate generalization to numerous generalized entropies within the literature. The fractal dimension of IE is identified in this paper. On another applicative note, this paper offers some potential applications of fractal dimension to smart cities. The paper ends with closing remarks combined with some challenging open problems and the next phase of research.

The construction safety risks (such as landslides or slumps) of the high-fill subgrade are characterized by uncertainty and variability. In order to ensure the construction safety of the high-fill subgrade of the expressway, a comprehensive risk assessment model of high-fill subgrade construction according to the combination weighting method based on game theory was established. Firstly, settlement rate, lateral differential settlement, horizontal displacement at the foot of the slope, deep horizontal displacement, and excess pore pressure were selected as evaluation indicators, and an evaluation index system of high-fill subgrade was constructed. Secondly, the subjective and objective weights were obtained via the analytic hierarchy process and entropy method. Furthermore, the optimized weights were obtained by introducing game theory, and the construction risk of the high-fill subgrade was evaluated and analyzed using the fuzzy comprehensive evaluation method. Finally, based on the high-fill section of the Zhijiang-Tongren Expressway in Hunan Province (China), the evaluation model was validated through field measurement data. The results show that the safety scores obtained using the three methods of analytic hierarchy process, entropy method, and combination weighting method based on game theory are similar. The combination weighting evaluation model can correct the evaluation result error caused by a single weight and avoid information delay caused by the manual processing and analysis of monitoring data. The high-fill subgrade safety evaluation grade based on the combination weighting method and game theory is consistent with the engineering situation, and its fault tolerance range is within 20%. The evaluation model proposed in this study can scientifically and effectively evaluate the safety risks of high-fill subgrade construction, significantly improving the safety and reliability during the construction process.

An exact solution for the Nagel-Schreckenberg model for v_max = 1 is known since the 90s, yet for v_max > 1 it remains an open question. It is conjectured here that this general solution can be generated from the basic solution (for v_max = 1) by a linear coordinate transformation, the shear mapping, which requires no additional parameters in the deterministic case, and two additional parameters otherwise. The proposed solutions show remarkable agreement with existing numerical solutions, except in the congested regime where the Monte Carlo data shows more concavity than the more linear congested branches predicted by the theory. More research is needed to investigate this bias.

This study aimed to analyze the competitive relationship among meetings, incentive, convention and exhibition (MICE) destinations with reference to the notion of niche businesses in New Zealand; and to explore the existence of cooperative strategies between neighboring destinations. The data were collected from Ministry of Business, Innovation and Employment Reports on the Convention Activity Survey (CAS) in New Zealand. The study contributes towards an innovative and better understanding of the dynamics of sustainable destination competitiveness. It broadens the scope of MICE industry research by exploring new insights on the notion of destination competition and makes a theoretical connection between niche theory and the importance of coopetition. By investigating the case of MICE destinations of four northern central islands in New Zealand, this study provides information on the strategic significance of niche marketing for global destinations preparing for entrance into this market.

To resolve the controversial issues of UV-light-initiatedcornealcollagen cross-linking (CXL) by theoretical formulas and measured clinical outcomes. The controversial issues are addressed and resolved by analytical formulas including: the validation of Bunsen Roscoe law (BRL), the cutoff light intensity, the minimum corneal thickness, the demarcation line depth, the role of oxygen riboflavin (RF) concentration. The overall CXL efficacy is governed by UV-A light intensity, dose, exposure time, mode of exposure (pulsed or CW), riboflavin concentration, diffusion and drops pre-operation and interoperation administration, concentration of oxygen in the stromal tissue (pre-op and inter-op), and environmental conditions. The length of the riboflavin presoaking time and viscosity of the riboflavin film also affect the crosslink depth. Analytic formulas are derived for the scaling laws for type-I and type-II efficacy, given by the square-root of light intensity, and light dose, respectively. The controversial issues of CXL may be partially resolved via analytic formulas, and compared with measurements. The scaling laws of type-I and type-II efficacy are different and given by analytic formulas. Our formulas also predict the maximum light intensity and the minimum corneal thickness, which are consistent with measurements.

The objective of this paper is to investigate the convergence of coupling-parameter expansion-based solutions to Ornstein-Zernike equation in liquid state theory. The analytically solved Baxter's adhesive hard sphere model is analyzed first using coupling-parameter expansion. It is found that the expansion provides accurate approximations to solutions - including the liquid-vapor phase diagram - in most parts of the phase plane. However, it fails to converge in the region where the model has only complex solutions. Similar analysis and results are, then, obtained using analytical solutions within the mean spherical approximation for the hard-core Yukawa potential. Next, convergence of the expansion is analyzed for the Lennard-Jonnes potential using an accurate density-dependent bridge function in the closure relation. Numerical results are presented which show convergence of correlation functions, compressibility versus density profiles, etc., in the single as well as two phase regions. Computed liquid-vapor phase diagrams, using two independent schemes employing the converged profiles, compare excellently with simulation data. Results obtained for the generalized Lennard-Jonnes potential, with varying repulsive exponent, also compare well with simulation data. All these results together establish the coupling-parameter expansion as a practical tool for studying single component fluid phases modeled via general pair-potentials.

It is due to Littlewood that the truth of the Riemann theorem implies that of the Lindel\"{o}f conjecture. This paper aims to use the idea of Littlewood to prove the Lindel\"{o}f conjecture for the Riemann zeta function. The Lindel\"{o}f $\mu $ function at the critical line is zero, with use of the Riemann theorem for the entire Riemann zeta function, proved based on the work of Heath-Brown. Our result is given to show that the Lindel\"{o}f conjecture, connected with the proof of the moment conjecture, is true.

This paper is our attempt on the basis of physical theory to bring more clarification on the question ``What is life?'' formulated in the well-known book of Schr\"odinger in 1944. According to Schr\"odinger, the main distinguishing feature of biosystem's functioning is the ability to preserve its order structure or, in the mathematical terms, to prevent increasing of entropy. Since any biosystem is fundamentally open, it is natural to use open system's theory. However, Schr\"odinger's analysis shows that the classical theory is not able to adequately describe the order-stability in a biosystem. Schr\"odinger should also appeal to the ambiguous notion of negative entropy. We suggest to apply the quantum theory. As is well-known, behaviour of the quantum von Neumann entropy crucially differs from behaviour of the classical entropy. We consider a complex biosystem $S$ composed of many subsystems, say proteins, or cells, or neural networks in the brain, i.e., $S=(S_i).$ We study the following problem: if the composed system $S$ can preserve the ``global order'' in the situation of increase of local disorder and if $S$ can preserve its entropy while some of $S_i$ increase their entropies We show that within quantum information theory the answer is positive. The significant role plays entanglement of the subsystems states. In the absence of entanglement, increasing of local disorder generates disorder increasing in the compound system $S$ (as in the classical regime).

In this paper, we solve KG-oscillator in the five-dimensional cosmic string space-time background with a uniform magnetic field and quantum flux subject to a scalar potential of Cornell-type using KaluzaKlein theory, and observe the gravitational analogue of the AharonovBohm effect. We show that the energy eigenvalue and eigenfunction depends on the global parameters of the space-time, and also a quantum effect is seen due to the dependence of magnetic field on the quantum numbers of the system

This contribution considers an improved control scheme for three-phase two-stage grid-tied photovoltaic (PV) power system based on integral sliding mode control (ISMC) theory. The proposed control scheme consists of maximum power point tracking (MPPT), DC-Link voltage regulation and grid currents synchronization. A modified voltage-oriented maximum power point tracking (VO-MPPT) method based on ISMC theory is proposed for design of an enhanced MPPT under irradiation changes. Moreover, a novel DC-Link voltage control based on ISMC theory is proposed in order to achieve good regulation of DC-Link voltage over its reference. To inject the generated PV power into the grid with high quality, a voltage oriented control based on space vector modulation (SVM) and ISMC (VOC-ISMC-SVM) has been developed to control the grid currents synchronization. Numerical simulations are performed in Matlab/SimulinkTM environment in order to evaluate the proposed control strategy. In comparison with conventional control scheme, the developed control strategy provides an accurate MPP tracking with less power oscillation as well as a fast and an accurate DC-Link regulation under climatic conditions variations. Moreover, the transfer of the extracted power into the grid is achieved with high quality.

This paper builds upon a theory of emerging-state actors using ISIS as a case study. This paper seeks to apply the theory in analyzing intervention & containment policies to use against emerging-state actors, using ISIS as the case study. Two baseline scenarios are used for evaluation – one replicating the historical foreign intervention against ISIS and a counter-factual where no foreign intervention occurred. Eleven contemporary military policies were tested against these baseline in isolation, combination, at different timing windows and under hypothetical “best case” conditions as well as operationally constrained. Insights of these tests include the influence of ethnographic envelopes, timing windows. Finally, a policy based on emerging-state actor theory is tested performing substantially better across primary measures than other policies or the historical baseline. This is compared against a falsified-policy designed to disprove that emerging-state actor theory contributed to the benefits. This paper’s contributions are a practical application of system dynamics simulations and systems-thinking to current problems, generate insights into the dynamics of emerging-state actors and intervention strategies, and demonstrate utility for future application of the underlying simulation in other scenarios involving non-state actor irregular conflict including terrorism, insurgents, or emerging-state actors.

We discuss the role of water bridging the DNA-enzyme interaction by resorting to recent 1 results showing that London dispersion forces between delocalized electrons of base pairs of DNA 2 are responsible for the formation of dipole modes that can be recognized by Taq polymerase. 3 We describe the dynamical origin of the high efficiency and precise targeting of Taq activity in 4 PCR. The spatiotemporal distribution of interaction couplings, frequencies, amplitudes, and phase 5 modulations comprise a pattern of fields instantiating the electromagnetic image of DNA in its 6 water environment, which is what the polymerase enzyme actually recognizes at long range. The 7 experimental realization of PCR amplification, achieved through replacement of the DNA template 8 by the treatment of pure water with electromagnetic signals recorded from viral and bacterial DNA 9 solutions, is found consistent with the gauge theory paradigm of quantum fields.

Pyrazinacenes are linearly fused heteroaromatic rings, with N atoms replacing all apical CH moieties. Component rings may exist in a reduced state having NH groups instead of N, causing cross-conjugation. These compounds have interesting optical and electronic properties, including strong fluorescence in the near infrared region and photocatalytic properties, leading to diverse possible applications in bio-imaging, organic synthesis as well as obvious molecular electronic uses. In this study, we have investigated the behaviour of seven-ring pyrazinacene 2,3,11,12-tetraphenyl-7,16-dihydro-1,4,5,6,7,8,9,12,13,14,15,16,17,18-tetradecaazaheptacene (Ph4H2N14HEPT) with emphasis on protic processes including oxidation, tautomerism, deprotonation and protonation, and the species resulting from those processes. We have used computational methods to optimize the structures of the different species and generate/compare molecular orbital structures. Aromaticity of species generated by the different processes has been assessed using the nucleus independent chemical shifts, and trends in the values have been associated with the different transformations of the pyrazinacene core. The computational data was compared with experimental data obtained from synthetic samples of the molecule tBu8Ph4H2N14HEPT.

This study investigates the influence of pyrolysis temperature on the main properties of BSG (brewer's spent grain) biochar and evaluates its suitability as an energy vector and as a substrate component. Pyrolysis tests were carried out at 673, 773, and 873 K. Bioenergy indexes were calculated for BSG and its biochar, and germination tests were carried out to obtain lentil sprouts. The results showed that the BSG biochar obtained at the lowest temperature biochar presented the best performance for use as biofuel. Regarding the germination tests, the different biochars were applied at 4 doses, and the evaluated parameters such as germination percentage, germination rate, mean germination time, and seed vigor were strongly influenced by the biochar addition. The biochar at 773 K added at a dose of 5% doubled the values of mean germination time, seed vigor, and time for 50% of the seeds to emerge compared to the control, constituted only with distilled water. The sustainable BSG valorization through pyrolysis reduces waste and contributes to circular economy practices by transforming industrial by-products into valuable resources for energy and agriculture. This approach highlights the importance of sustainability in reducing the environmental impact of industrial waste and promoting renewable energy sources.

In this paper, we investigate the so-called electronic dressed states, a unified quasiparticle resulting from the interaction between electrons in a two-dimensional material with an off-resonance optical dressing field. If the frequency of this field is much larger than all characteristic energies in the system, such as the Fermi energy or bandgap(s), the electronic band structure is affected by radiation so that some important properties of the electron dispersions could be modified in a way desirable for practical applications. For example, a circularly polarized light can be used to vary the bandgap of Dirac materials: it opens a gap in graphene and other metallic and semimetallic lattices, or modifies the magnitude of an existing gap. This will either enhance or reduce a gap, depending on its initial value as well as properties of a host material. Here, we consider gaped dice and Lieb lattices as samples, and put forward a full theoretical model to reveal how these electronic states are deformed by an elliptically-polarized irradiation with a focus on generation and modification of a bandgap.

This study explores the role of stakeholder engagement in enhancing supply chain sustainability within the renewable energy sector. Through a qualitative research approach, including in-depth interviews with key stakeholders such as government agencies, industry associations, renewable energy companies, community groups, and environmental organizations, the research reveals the complexity and significance of effective stakeholder engagement. Stakeholders highlighted diverse motivations, including environmental, social, economic, and regulatory concerns, driving their participation. The study underscores the importance of tailored engagement strategies that recognize stakeholder heterogeneity and address specific needs and expectations. Collaborative approaches, such as public-private partnerships and multi-stakeholder initiatives, were identified as crucial for pooling resources, sharing knowledge, and addressing common challenges. However, challenges related to power imbalances, conflicting interests, and communication barriers were also noted. Government policies and regulatory frameworks were found to play a pivotal role in shaping stakeholder engagement practices and sustainability outcomes. Regulatory uncertainty and inconsistency were cited as significant concerns that could undermine sustainability initiatives. Community engagement emerged as a critical factor, with local communities often directly impacted by renewable energy projects. Meaningful engagement, including consultation and benefit-sharing mechanisms, is essential for building trust and securing social acceptance. Emotional intelligence and marketing strategies were recognized as important tools for effective stakeholder engagement, emphasizing the role of empathy, active listening, and clear communication. The findings of this study highlight the need for a holistic and integrated approach to stakeholder engagement and supply chain sustainability in the renewable energy sector. By addressing diverse stakeholder needs, fostering collaboration, and aligning policies with sustainability goals, stakeholders can work together to accelerate the transition towards a more sustainable energy future.

Deploying onshore wind energy as a cornerstone of future global energy systems challenges societies and decision-makers worldwide. Expanding wind energy should contribute to a more sustainable electricity generation without harnessing humans and their environment. Opponents often highlight the negative environmental impacts of wind energy to impede its expansion. This study reviews 152 studies to synthesize, summarize, and discuss critically the current knowledge, research gaps, and mitigation strategies on the environmental impacts of onshore wind energy. The investigated effects comprise impacts on the abiotic and biotic environment, with birds and bats in particular, noise and visual impacts. Effects are discussed in the context of social acceptance, other energy technologies, and wind energy expansion in forests. The review illustrates that many effects are highly case-specific and must be more generalizable. Studies are biased regarding the research focus and areas, needing more standardized research methods and long-term measurements. Most studies focus on the direct mortality of birds and bats at wind farms and are concentrated in Europe and North America. Knowledge gaps persist for many impact categories, and the efficacy of mitigation strategies has yet to be proven. More targeted, unbiased research is required that allows for an objective evaluation of the environmental impacts of wind energy and strategies to mitigate them. Impacts, such as those on biodiversity, need to be addressed in the context of other anthropogenic influences and the benefits of wind energy. This forms the basis for a socially acceptable, efficient, and sustainable expansion of wind energy.

Demand flexibility plays a crucial role in mitigating the intermittency of renewable power sources. This paper focuses on an active distribution grid that incorporates flexible heat and electric demands, specifically Heat Pumps (HPs) and Electric Vehicles (EVs). Additionally, it addresses Photovoltaic (PV) power generation facilities and electrical batteries to enhance demand flexibility. To exploit demand flexibility from both heat and electric demand, along with the integration of PVs and batteries, Control and Communication Mechanisms (CCMs) are formulated. These CCMs integrate demand flexibility into the distribution grids to get economic benefits for private households and at the same time facilitate voltage control. Concerning EVs, the paper discusses voltage-based droop control, scheduled charging, priority charging, and up-/down-power regulation to optimize the charging and discharging operations. For heat demands, the on-off operation of the HPs integrated with Phase Change Material (PCM) storage is optimized to unlock heat-to-power flexibility. The HP controllers aim to ensure as much self-consumption as possible and provide voltage support for the distribution grid while ensuring the thermal comfort of residents. Finally, the developed CCMs are implemented on a small and representative community of active distribution grid with 8 houses using Power Factory software and DigSILENT Simulation Language (DSL). This scalable size of the active distribution network facilitates to carefully study symbiotic interaction among the flexible load, generation, and different houses thoroughly. The simulation results confirm that the integration of flexible demands into the grid using the designed CCMs results in the grid benefiting from stabilized voltage control, especially during peak demand hours.

In 2023, residential and commercial sectors together consumed approximately 27.6% of total U.S. energy, equivalent to about 20.6 quadrillion Btu. Factoring in the electrical system energy losses, the residential sector represented approximately 19.7% of total U.S. energy consumption during that time. There were approximately 144 million housing units in the United States in 2023, which is increasing yearly. In this study, information on energy usage in the United States (U.S.) residential sector has been analyzed and then represented as energy intensities to establish benchmark data and to compare energy consumption of varying sizes and locations. First, public sources were identified, and data from these previously published sources were aggregated to determine the energy use of the residential sector within the US. Next, as part of this study, the energy data for seven houses/apartments from five different United States climate zones were collected firsthand. That data was analyzed, and the energy intensity of each home was calculated and then compared with the energy intensities of the other homes in the same states using RECS data. The energy intensity for each facility was calculated based on the actual energy bills. Finally, the study evaluated the carbon footprint associated with residential energy consumption in all 50 states to reinforce the importance of sustainable development initiatives.

This research aimed to determine the most viable locations for establishing solar energy facilities in Yemen through the utilization of the Analytical Hierarchy Process (AHP), Best-Worst Method (BWM), and Geographic Information System (GIS). A total of twelve key criteria were meticulously selected and evaluated based on their impact on the appropriateness of sites for solar power plants. These criteria were amalgamated using a weighted overlay tool, resulting in a map that classified regions as either optimal, highly suitable, or suitable. The findings of the study indicated that the eastern, southern, and northern parts of Yemen are prime candidates for solar energy installations due to their moderate climate and flat topography. On the other hand, the western regions were deemed less favorable. The breakdown of site classifications revealed that 38% of areas were optimal, 61% were highly suitable, and only 1% were considered suitable, based on the assigned weights from the AHP and BWM methodologies. Moreover, a sensitivity analysis was carried out to evaluate the impact of adjusting the weights of Global Horizontal Irradiance (GHI) and slope on site classifications. A minor increase in the weights of GHI (from 30% to 31%) and slope (from 10% to 11%) resulted in a significant alteration in the suitability categories, highlighting the importance of weight adjustments in multi-criteria decision-making processes. In conclusion, the study emphasizes the effectiveness of AHP, BWM, and GIS in assessing site suitability for solar energy facilities, as well as the significance of sensitivity analyses. These approaches provide valuable insights for decision-makers, aiding in strategic planning and fostering sustainable energy development in Yemen.

This study aimed to evaluate a cantilever beam-type piezoelectric energy harvester operating on train-induced vibrations for powering Wireless Sensor Networks (WSNs) used in railway track monitoring systems. The harvester's behaviors under different conditions are simulated in MATLAB using the analytical model. Natural frequency, maximum deflection, and stress were calculated with greater precision using eigenfrequency and stationary analysis using COMSOL Multiphysics. At a base excitation of 2 g and a resonant frequency of 4.38 Hz, the simulated results showed that the developed energy harvester prototype could generate up to 14 V of AC output voltage and 550 mW of output power. These findings highlight the promising potential of the proposed energy harvester for transforming train mechanical energy into electrical power. This energy harvester's viability and dependability for real-world applications in monitoring railway tracks are supported by developed analytical and simulation models.

As the global transition towards renewable energy accelerates, the integration of grid-scale energy storage systems has become increasingly critical for stabilizing energy supply and enhancing grid reliability. Among various storage technologies, lithium-ion batteries stand out for their high energy density, scalability, and relatively low environmental impact. This study investigates the performance and longevity of lithium-ion batteries in grid-scale applications, focusing on the impact of operational parameters such as cycling frequency, depth of discharge, temperature fluctuations, and charging/discharging rates. Employing a mixed-methods approach, we combined quantitative analysis of performance metrics (cycle life, capacity fade, efficiency) with qualitative assessments from case studies of existing grid-scale projects. Our findings reveal that while lithium-ion batteries exhibit robust performance in grid-scale storage, their longevity and efficiency are significantly influenced by operational conditions. Specifically, temperature management and optimized cycling strategies were identified as key factors in mitigating degradation and extending battery life. This research provides a comprehensive understanding of lithium-ion battery behavior in grid-scale environments, offering valuable insights for the design, optimization, and management of energy storage systems. By addressing the challenges of battery performance and longevity, our study contributes to the development of more sustainable and reliable grid storage solutions, facilitating the broader adoption of renewable energy sources.

In this paper, we study the constrained minimization problem for an energy functional which is related to the following Kirchhoff type equation \begin{equation*} -\Big(\eta+b\big(\int_{\R^{3}}|\nabla u|^{2}dx\big)^{s}\Big)\Delta u+V(x)u=\mu u +\lambda|u|^{p}u,\end{equation*} where $b$ is a positive constant, parameters $\eta\geq0, \lambda>0$, exponents $s>0$, $0

The global energy landscape is undergoing a transformative shift, and the potential of LNG as a major energy source is a topic of intense debate. In order to meet the growing demand for sustainable energy supply, it is crucial to maximize the efficiency and environmental friendliness of the LNG supply chain. This research aims to leverage computational modeling and optimization techniques to enhance the production units involved in LNG production. By harnessing the power of advanced algorithms and simulations, we can identify and implement innovative strategies that minimize energy consumption, reduce greenhouse gas emissions, and enhance the overall sustainability of LNG. Through this study, we seek to uncover novel approaches to address the challenges faced by the LNG industry, including improving operational efficiency, optimizing liquefaction processes, and enhancing the utilization of natural resources. By integrating cutting-edge computational tools and considering environmental factors, we aspire to pave the way for a more sustainable and environmentally friendly future powered by LNG. By exploring the immense potential of computational modeling and optimization, we strive to contribute to the ongoing efforts in advancing energy sustainability and shaping the future of LNG as a crucial global energy source."In this paper, our focus is on simulating and optimizing the process of converting natural gas to LNG. Our goal is to achieve the minimum energy consumption per ton of LNG produced. Through our research, we have identified that utilizing a three-stage exchanger is the most effective approach for minimizing energy consumption in an LNG industrial production unit. Moreover, we have discovered that the outlet pressure from the compressor and the type of refrigerant in the cooling system play significant roles in determining the rate of energy conservation. By carefully considering these factors and optimizing their settings, we can further enhance the overall energy efficiency of the LNG production process. Our research aims to provide valuable insights and guidance to industry professionals and decision-makers in the LNG sector. By implementing the findings of this study, we can contribute to the sustainable development and utilization of LNG as a cleaner and more environmentally energy source. Friendly It's great to see the optimized parameters for the refrigerants and pressure settings in the liquefaction and subcooling cycles. With the mass fraction of 0.89 for methane and 0.14 for ethane in the liquefaction cycle, and 0.59 for methane and 0.3 for nitrogen in the composition for achieving energy efficiency in the LNG production subcooling cycle, The optimized outlet pressure of 650 kPa for the compressors in the liquefaction cycle and 1800 kPa for the subcooling cycle furtherr ccontribute to minimizing energy consumption. Based on your findings, the amount of consumed energy at 14.81 kW per ton of produced LNG highlights the success of the optimization efforts. Reducing the energy consumption per ton of LNG produced is a significant accomplishment towards achieving energy sustainability and environmental friendliness in the LNG industry. These results demonstrate the importance of computational modeling and optimization in identifying the best parameters for eenhancing energy efficiency in LNG production. By implementing these optimized settings, we can work towards a more sustainable future with reduced energy consumption and lower environmental impact

The paper presents a thorough examination of the burgeoning field of utilizing manufacturing waste for sustainable energy generation, aligning with the global imperative for resource efficiency and clean energy solutions. With the manufacturing sector being a significant contributor to waste generation, this study explores innovative approaches to transform waste materials into valuable resources, thereby mitigating environmental impacts and contributing to a circular economy. This work critically reviews current trends, emphasizing technological advancements, policy interventions, and market dynamics shaping the manufacturing waste utilization landscape. Noteworthy developments, such as advanced sorting technologies and the integration of digital solutions, are discussed in detail, showcasing their role in enhancing the efficiency of waste management processes. The study outlines future trends in the field, anticipating a shift towards closed-loop systems guided by circular economy principles. This comprehensive review aims to contribute to the discourse on sustainable waste management and energy generation by providing a holistic perspective on the field's current state and offering insights into the future trajectories that will propel manufacturing waste toward a more sustainable and circular future. The synthesis of technological innovation, collaborative efforts, and evolving regulatory frameworks presents a compelling case for the continued exploration of manufacturing waste as a valuable resource in the pursuit of a more sustainable and energy-efficient world.

In this study, a novel two-layer control scheme aimed at enhancing the dynamic performance of a nonlinear vehicle through the utilization of an optimal control approach grounded in predictive control principles is presented. The first layer of our control system focuses on the computation of an optimized rotational torque that ensures lateral dynamic stability. This torque is subsequently translated into differential forces acting on the wheels, employing the inverse tire model to derive the desired longitudinal slips. These slip values are then transmitted to the second layer of our control system. In the second layer, the electric motors associated with the vehicle's wheels dynamically adjust the input torque to accurately track the desired slip, thereby ensuring the overall stability of the electric vehicle. In view of the paramount importance of energy consumption in electric vehicles, we adopt optimal control strategies to substantially minimize battery utilization. To this end, careful selection of appropriate weighting coefficients in the control laws enables us to maintain the electric motors within their permissible operational range while simultaneously minimizing battery energy consumption for desired slip tracking. Extensive simulation results validate the effectiveness of our proposed control system in proficiently managing nonlinear effects and safeguarding the vehicle's stability.

In this study, the potential of Fe3Al coating material as an environmentally friendly alternative to coatings containing critical elements for brake discs was investigated. A buffer layer of Cr-Mo steel (Ferro 55) was applied to enhance coating quality and prevent the formation of hot cracks during solidification. Microstructural analysis of the cross-section of the coating showed that the buffer layer diffused into the Fe3Al coating, forming a combination of Fe3Al, Fe, and Fe3AlC0.5 phases. The tribological properties of the Fe3Al coating were evaluated by pin-on-disc tests using two different copper-free friction materials extracted from commercial brake pads. The wear results showed a coefficient of friction comparable to that of an uncoated disc, but with a reduction in Particulate Matter (PM) emissions, an interesting aspect that is gaining increasing importance in view of the upcoming international standards..

This analysis focuses on identifying the most efficient and cost-effective method of supplying power to a remote site, exploring photovoltaics (PV) and small wind turbines as primary power sources, and evaluating battery banks and hydrogen storage fuel cell systems as potential storage options. The hydrogen storage system converts surplus renewable power into hydrogen through an elec-trolyzer, storing it for later use in a fuel cell when renewable sources produce less power, enabling efficient energy storage during peak production periods. A sensitivity analysis of wind speed and hydrogen subsystem cost was conducted to evaluate the hydrogen storage system's performance. The optimal system graph suggests that the hydrogen subsystem must significantly decrease in cost to rival the battery bank, and in most cases, both the hydrogen system and battery bank were recommended together, offering reliable and efficient power for the remote site. While the battery bank is presently the more feasible option for powering the remote site, continuous monitoring and evaluation of both systems, considering site location, energy needs, and available resources, are essential to determine the most suitable power supply approach as technology advances and costs evolve over time.

To improve the accuracy of short-term multi-energy load prediction models for integrated energy systems, the historical development law of the multi-energy loads must be considered. Moreover, understanding the complex coupling correlation of the different loads in the multi-energy systems and accounting for other load-influencing factors, such as weather, may further improve the forecasting performance of such models. In this study, a two-stage fuzzy optimization method is proposed for the feature selection and identification of the multi-energy loads. To enrich the information content of the prediction input feature, we introduced a copula correlation feature analysis in the proposed framework, which extracts the complex dynamic coupling correlation of multi-energy loads and applies Akaike information criterion (AIC) to evaluate the adaptability of the different copula models presented. Furthermore, we combined a NARX neural network with Bayesian optimization and an extreme learning machine model optimized using a genetic algorithm to effectively improve the feature fusion performances of the proposed multi-energy load prediction model. The effectiveness of the proposed short-term prediction model was confirmed by the experimental results obtained using the multi-energy load time-series data of an actual integrated energy system.

In recent years, unquestionable warnings like the negative impacts of CO2 emissions, the necessity of utilizing sustainable energy sources, and the rising demand for municipal electrification have been issued. In this study, by incorporating two significant assumptions, such as electricity production in close proximity to the business location and only renewable energy resource usage, a modest off-grid hybrid energy system is designed. To construct the system, a number of elements such as wind generators (WG), photovoltaic arrays (PV), battery banks, and bi-directional converters are taken into account. Moreover, a real case in Malmö, Sweden, is considered. To optimize the system, a bi-objective problem is developed, and it is solved by proposing a particle swarm optimization (PSO) approach to provide the load requirements (with a maximum allowance of 0.1% unmet) for a nearby supermarket (approximately 1000 m2). Moreover, to verify the obtained results, the developed system is simulated using HOMER Pro software, and the results are compared and discussed. The contribution of this study is to provide off-grid or local clients around the world with a dependable and affordable option by minimizing both the baseline cost of energy and the net current expenditure in the desired system. The best-obtained results by the proposed PSO offered 160 PVs, 5 WGs, and 350 batteries, respectively, while the best solution found by the simulation method was using 384 PVs, 5 WGs, and 189 batteries for the considered off-grid system.

The use of smart grids has enabled a number of planning methods to be developed to optimize energy costs, Peak to Average Ratios (PARs), and consumer satisfaction for load management in industrial, commercial, and domestic sectors. From a technical point of view, achieving optimal outcomes requires Demand Side Management (DSM). In smart grids, utility companies and electric users communicate two-way using digital technology to make a sustainable and economic system. This paper proposes a novel framework within which an Energy Management Controller (EMC) keeps track of each appliance, its operational time, and the costs associated with them. Customers of smart grids are motivated to shift their Off-Peak Hours (OPH) from Peak Hours by presenting incentives in OPH. The metering devices would also save customers costs by preventing load shifting between high- and low-cost periods. In addition, the study proposes the bacterial foraging algorithm and grasshopper optimization algorithm for lessening power price and PAR without compromising user comfort (UC) through appliance planning. The simulation results on a practical test system advocate the high effectiveness and reliable performance of the proposed model.