The There are many factors influencing the performance of photovoltaic (PV) systems. Among these factors, temperature and solar radiation are two major parameters that have a large effect on the efficiency of PV systems. The cell temperature of PV panels is related to the ambient temperature while the solar radiation incident on the surface of the PV modules depends on the slope and azimuth of these modules. Furthermore, ground reflectance (albedo) affects the irradiance incident on the PV panel surface, which in turn affects the output of a PV system. Nevertheless, the effects of these factors on the economic performance of the solar PV systems are scarcely reported. This paper presents a complete design of a stand-alone PV/battery system to supply electric power for a mobile base station in Choman, Erbil, Iraq. The effects of different factors on the total electricity produced by PV arrays and its economic performance are simultaneously investigated. HOMER software has been used as a tool for the techno-economic and environmental analysis. As indicated from the simulation results, the PV array capacity and its economic performance are highly affected by the variation of the slope and azimuth. With a base case (albedo of 20% and average annual ambient temperature of 11°C), the best feasible system which is achieved by facing PV due to south with a tilt angle of 40° or 45°, is found to have net present cost (NPC) of 70595 $ and cost of energy (COE) of 0.54 $/kWh. Moreover, the results indicate that increasing the ground reflectance from 10% to 90% results in a 7.2% decrease in the PV array capacity and about 3% decrease in the NPC and COE. On the other hand, increasing the ambient temperature from 0°C to 40°C results in a 19.7% increase in the PV array capacity and an 8.2% increase in the NPC and COE. Furthermore, according to the ambient temperature of Choman, using PV modules with high sensitivity to temperature is found to be an attractive option. Provided simulation performance analysis proves that the studied parameters must be treated well to establish an enabling environment for solar energy development in Iraq.

Solar concentrator photovoltaic collectors are able to deliver energy at higher temperatures for the same irradiances, since they are related to smaller areas for which heat losses occur. However, to ensure the system reliability, adequate collector geometry and appropriate choice of the materials used for all their components will be crucial. The present study focuses on the re-design of the C-PV collector reflector currently produced by the Swedish company Solarus AB, together with a comparative analysis based on the annual assessment of the solar irradiance in the collector. An open-source ray tracing code (Soltrace) is used to accomplish the modelling of optical systems in concentrating solar power applications. Symmetric parabolic reflector configurations are seen to improve the PV system performance when compared to the conventional structures currently used by Solarus. The parabolic geometries, using either symmetrically or asymmetrically placed receivers inside the collector, achieve both the performance and cost-effectiveness objectives: for almost the same area or costs, the new proposals for the PV system may be in some cases 70 % more effective as far as energy output is concerned.

Energy management strategy (EMS) is a decision-making algorithm for effective power allocation between storage devices in a hybrid energy storage system (HESS). Source voltages, state-of-charge (SOC), terminal voltage of load, and rate of change of battery current must be considered while implementing EMS and hence they are termed as performance indicators. This paper presents the development of an EMS designed to manage the performance indicators of the sources and ensure efficient power distribution through a shared bus topology. A shared bus topology employs individual converters for each source, offering efficient control over these sources. Rule-based fuzzy logic control ensures efficient power distribution between batteries and ultracapacitors. Additionally, hardware has been developed to validate the power-allocation strategy and regulate the DC-link voltage in the Energy Management System (EMS). The dSPACE MicroLabBox is utilized for the implementation of real-time control strategies. A battery and an ultracapacitor bank are utilized in a Hybrid Energy Storage System. The simulation outcomes have been corroborated by experimental data, affirming the efficacy of the proposed energy management strategy.

ABSTRACT The work is focused on determining the energy transfer from EV’s to grid for different operating conditions. The study has been simulated on a scaled model and later validated through experimental tests on batteries of 20 kWh, 40 kWh, 60 kWh and 80 kWh for EV’s energy rates from 130 Wh/km to 180 Wh/km. Tests have been developed to evaluate the energy transfer from driving distance between 0 and 50 km. Results have proved there is a linear dependence between energy transfer and energy rate. Experimental and simulated values have been correlated showing a 99.6% accuracy. The ratio of energy transfer to battery energy capacity depends not only on this latter parameter, but also on the energy rate of the electric vehicle. Experimental tests have shown a variation from a minimum transfer ratio of 54.1% for the highest electric vehicle energy rate and lowest battery energy capacity and power transfer to grid rate to a maximum of 88.6% for the highest power transfer to grid rate and battery energy capacity and lowest electric vehicle energy rate.

In current electric vehicles, the traction battery is intended to store energy. When designing this battery different parameters must be taken into account in order to arrange the battery/module/cells in the mechanically and thermally safest configuration. Moreover, the battery layout must have a correct dynamic behavior in possible collisions. In the present study, different battery configurations plus added energy absorbers are analyzed. In order to do that, an internal combustion vehicle modeled with finite elements is applied as the reference model. The structural behavior of the different battery configurations in the event of a side collision is examined. Firstly, the safest arrangement is stablished, both with respect to cabin intrusion and thermal runaway propagation. Secondly, the safest arrangement that guarantees the safety of the occupants in the event of a side collision is analyzed but using the MADYMO. This software includes experimentally validated dummies which allow have an insight in the stresses experienced by occupants. On the one hand, the analysis states that the battery pack inclusion in the vehicle increases the stiffness of the car floor, resulting in fewer intrusions in the passenger compartment. Therefore, a greater safety for the occupants is reached. On the other hand, none of the configurations analyzed has shown enough safety against the phenomenon of Thermal Runaway.

Li-ion battery packs are the heart of modern electric vehicles. Due to their perishable nature, it is crucial to supervise them closely. In addition to on-board supervision over safety and range, insights into the battery’s degradation are also becoming increasingly important, not only for the vehicle manufacturers but also for vehicle users. The concept of digital twins has already emerged on the field of automotive technology, and can also help to digitalize the vehicle’s battery. In this work, we set up a data pipeline and digital battery twin to track the battery state, including state of charge (SOC), state of health (Capacity) (SOHc ) and state of health (Resistance) (SOHr ). To achieve this goal, we reverse-engineer the diagnostics interface of a 2014 e-Golf to query for Unified Diagnostic Services (UDS) messages containing both battery pack and cell-individual data. An on-board diagnosis (OBD) logger records the data with edge-processing capability. Pushing this data into the cloud twin system using IoT-technology, we can fit battery models to the data and infer cell individual internal resistance from them. We find that the resistances of the cells differ by a magnitude of two. Furthermore, we propose an architecture for the battery twin in which the twin fleet shares resources like models by encapsulating them in Docker containers run on a cloud stack. By using web technology, we present the analyzed results on a web interface.

Motivated by experiments, we undertake an investigation of electronic structure reconstruction and its link to electrodynamic responses of monoclinic MoO$_2$. Using a combination of LDA band structure with DMFT for the subspace defined by the physically most relevant Mo $4d$-bands, we unearth the importance of multi-orbital electron interactions to MoO$_2$ parent compound. Supported by a microscopic description of quantum capacity we identify the implications of many-particle orbital reconstruction to understanding and evaluating voltage-capacity profiles intrinsic to MoO$_2$ battery material. Therein, we underline the importance of the dielectric function and optical conductivity in the characterisation of existing and candidate battery materials.

The current work investigates how adding a battery of optimal capacity to a grid-connected photovoltaic (PV) system can improve its economic feasibility. Also, the effect of different parameters on the feasibility of the PV system was evaluated. The OBC was determined for different saving targets of the annual electricity consumption of the chosen building. For this aim, real electricity consumption data of a residential building in Landskrona, Sweden, was used as energy consumption profile. Solar World SW325XL, which is a monocrystalline solar panel, was selected as PV panels. The calculations were performed under the metrological and economic conditions of southern Sweden. Different working parameters (WP)were considered (prices of the battery, feed-in tariffs, and saving targets). The performed calculations show that the optimal battery capacity (OBC), in which the payback time (PBT) of the system is maximized, strongly depends on the WP. The proper selection of the battery can considerably increase the economic feasibility of the PV system in southern Sweden. However, in some cases, using battery can have a negative impact on the PBT of the system. The results show that the electricity price, the module price, the inverter price, and the inverter lifetime have the highest effect on the PBT.

The polymer binder, poly(imide-co-siloxane) (PIS), was synthesized and applied to form a thin cathode layer composites for a thermal battery that has an unusually high operating temperature of 450 °C. The PIS was prepared through cross-linking of the polyimide with polysiloxane. The morphology of FeS₂/PIS composites showed that FeS₂ particles was coated with the PIS cross-linked gel. The FeS₂/PIS composites enabled to fabricate mechanically stable thin cathode layer that was 20–10% of the thickness of a conventional pellet-type cathode. The FeS₂/PIS composites were stable up to 400 °C and maintained their morphology at this temperature. PIS coating layers decomposed at 450 °C and a new residue was generated, which was observed by transmission electron microscopy and the compositional change was analyzed. The FeS₂/PIS composites showed enhanced thermal stability over that of FeS₂ in thermogravimetric analysis. The thermal battery with the PIS polymer binder showed a 20% discharge capacity increase when compared to a conventional pellet-type cathode.

The separator membrane is an essential component of lithium-ion batteries, separating the anode and cathode and controlling the number and mobility of the lithium ions. Among the polymer matrices most investigated for battery separators are poly(vinylidene fluoride) (PVDF) and its copolymers poly(vinylidene fluoride-co-trifluoroethylene) (PVDF-TrFE), poly(vinylidene fluoride-co-hexafluoropropylene) (PVDF-HFP), and poly(vinylidene fluoride-cochlorotrifluoroethylene) (PVDF-CTFE), due to their excellent properties such as high polarity and the possibility of controlling the porosity of the materials through binary and ternary polymer/solvent systems, among others. This review presents the recent advances on battery separators based on poly(vinylidene fluoride) (PVDF) and its copolymers for lithium-ion batteries. It is divided in the following sections: single polymer and co-polymers, surface modification, composites and polymer blends. Further, a critical comparison between those membranes and other separator membranes is presented, as well as the future trends on this area.

This paper aims to present a smart high speed battery charger, powered by a photovoltaic module array, for a LiFePO4 battery as a solar energy storage device. With a battery charging strategy, the presented battery charger involves a Buck converter as the core equipped with a simple maximum power point (MPP) tracker. Considering complexity reduction and easy hardware implementation, a constant voltage MPP tracking approach is adopted such that the maximum amount of output power can be delivered to the load in response to an arbitrary change in the solar radiation. A smart two-stage charging strategy, with a constant current mode followed by a constant voltage mode, is employed in such a way that the battery charge process can be accelerated largely, while the damage caused by overcharging can be prevented. In the end, the performance of this proposal is validated experimentally.

In the future, the pursuit of high-quality economic development and a focus on ecological environmental protection in China will inevitably result in significant conflicts between land use and ecological land use. The challenge lies in achieving sustainable high-quality development while simultaneously protecting the ecological environment, optimizing the land use structure, and promoting a harmonious relationship between humans and the land. These challenges are faced by all regions. Land use conflicts primarily occur in peri-urban areas characterized by prominent economic development and urban agglomeration. Previous studies have mainly focused on analyzing the effects of land use on habitat quality during intense urbanization. However, it is important to recognize that land pressure encompasses economic, ecological, and social aspects. To gain a comprehensive understanding of the spatial conflict of land use and the impact on habitat quality in Ankang, a city that has been advocating ecological protection for the past two decades, this study aims to objectively analyze the spatial trends in land use changes in such cities. Additionally, it aims to provide insights for the harmonious development of land use in eco-region-oriented cities. Using the SSP-RCP scenarios provided by CMIP6, this paper employs a system analysis method, PLUS model, InVEST model, and land use conflict measurement model to dynamically simulate the future habitat quality and spatial conflict patterns of land use in Ankang City. The study explores the spatial coupling effect of both factors under different scenarios. The results indicate the following:(1) Under different future shared socio-economic path scenarios, land use intensity and land conflict levels follow the order of SSP585 (high forcing scenario), SSP370 (medium to high forcing scenario), SSP245 (medium forcing scenario), and SSP126 (low forcing scenario), with intensity and conflict decreasing accordingly. (2) The overall development trend in Ankang City reveals an intensification of land use conflicts and a decrease in habitat quality. The expansion rate of construction land is increasing and exhibiting aggregation, while agricultural land area is expanding and forest land area is continuously decreasing. (3) Land use intensity exhibits a significant positive correlation with land conflict levels, while land conflict levels demonstrate a significant negative correlation with habitat quality. These findings suggest that land use has had some impact on the ecological environment, with indications of habitat degradation. Even in Ankang, where ecological development is highly valued, the city will gradually face conflicts between ecological protection and economic development in future scenarios. The study highlights that Ankang's future development space will be constrained within the context of environmental protection, leading to greater land use conflicts in urban and surrounding areas. Consequently, the quality of habitats will inevitably decline. Therefore, it is crucial to allocate sufficient space for economic development while simultaneously prioritizing ecological protection. This approach will ensure a healthy economic development trajectory and foster a harmonious relationship between humans and the land.

Our work is regarding the analysis of land use changes, in the light of “saving soil” against the expansion due to unearned plus value of land: The loss of natural and agricultural surface in front of the expanding urban environment is a critical aspect of unsustainability of urban development, especially in the way it was carried out in the past decades. The measure of the physical transition of land use and characters from a more natural condition of land surface to a new artificial one, joint with a parallel analysis of the increase of land value due to such change is nowadays a major land-policy tool. The interplay of urban economics regulation with planning, reveals new key issues in urban governance and environmental preservation. In this paper it will be shown some experiment about the impact assessment of soil take, related with the seek of valorization of property inside the planning process. Our paper reports as well about the experimental activity carried out inside the MITO Lab of the Polytechnic of Bari, where reports about property values and environmental values have been produced, specially looking at the reality of the Apulia, a southern Italian Region, that is rich of farmlands and coastlines, often invaded by constructions with a severe loss of nature, landscape and ecosystems services.

The greenhouse gases and air pollution generated by extensive energy use have exacerbated climate change. An electric-bus (e-bus) transportation system favors reducing pollution and carbon emissions. This study analyzed the minimization of construction costs for an all battery-swapping public e-bus transportation system. A simulation was conducted according to existing timetables and routes. Daytime charging was incorporated during the hours of operation; the two parameters of the daytime charging scheme were the residual battery capacity and battery-charging energy during various intervals of daytime peak electricity hours. The parameters were optimized using three algorithms: particle swarm optimization (PSO), a genetic algorithm (GA), and a PSO–GA. This study observed the effects of optimization on cost changes (e.g., number of e-buses, on-board battery capacity, number of extra batteries, charging facilities, and energy consumption) and compared the plug-in and battery-swapping e-bus systems. The results revealed that daytime charging can reduce the construction costs of both systems. In contrast to the other two algorithms, the PSO–GA yielded the most favorable optimization results for the charging scheme. Finally, according to the cases investigated and the parameters of this study, the construction cost of the plug-in e-bus system was lower than that of the battery-swapping e-bus system.

Building integrated photovoltaics (BIPV) consists of PV panels that are integrated into the building as part of the construction. This technology has advantages such as the production of electricity without necessary additional land area. This paper provides a literature review about the recent developments in urban building energy modelling, including tools and methods, and how they can be used to predict the effect of PV systems on building outdoor and indoor environments. It is also intended to provide a critical analysis on how PV systems affect the urban environment, both from an energy and a comfort point of view. The microclimate, namelly the urban heat island concept, is introduced and related with the existence of PV systems. It is concluded that urban building energy modelling (UBEM) can be effective to study the performance of PV systems in the urban environment. It allows to simultaneously predict the building energy performance and the microclimate effect. However, there is a need to develop new methodologies to overcome the challenges associated to UBEM, especially in what concerns non-geometric data, which leads to a major source of errors. and to find an effective method to predict the effect of PV systems in the urban environment.

Solar photovoltaic systems (PVs) are becoming more popular in Poland, as the country aims to increase its share of renewable energy sources and reduce its dependence on coal. According to the official data the total installed PV capacity in Poland reached 15.6 GW in September 2023 while at the end of 2020 it was 4.1 GW. This situation was caused by many factors, but mainly by government subsidy programs for households and rising electricity prices. A number of photovoltaic installations with a capacity of up to 50 kWp were carried out, although the installation should always be adapted to the needs of a given household. Estimating the yield of solar energy systems is crucial for that. It can be done by several methods, but always as initial step in modelling of solar energy systems weather data, especially solar irradiation is required. To get this data we can arrange the measurement from ground stations or use reanalysis models and satellite-derived datasets. There are several different datasets, both public and commercial, of solar irradiance data ready to use. This data provides insights into the average solar irradiance levels throughout the year, aiding in estimating the energy generation capacity. The paper contributes the knowledge of energy generation capacity that can be quickly counted for a solar PV micro-system with different orientation and inclination as a multiplier of the energy value obtained from a solar PV system of 1 kW-peak for a significant number of locations in Poland based on open-source solar irradiation data

The power system has rapidly grown and expanded over the past decades and has been experiencing major changes and challenges. The increase in energy demand and the modern advancements in the smart grid, such as solar and wind energies and electric vehicles, have led to complexity and complications for utilities. A further layer of complexity and difficulty was added by the rapid expansion of behind-the-meter (BTM) photovoltaic (PV) systems with various designs and characteristic features. The rapid increase and the invisible solar power (BTM) have led to fluctuations in power grid stability and reliability and to inefficiency. Accurate forecasting of load generation will help to assure optimal planning, minimize the negative effects of the PV systems, and minimize the operational and maintenance costs. The authors propose a solution that uses combinations of K-means clustering with neural network machine learning models, AMI real-world PV load generation, and weather data to forecast the generation load at customer locations to achieve a 2.49% error between actual and predicted generation load.

Building energy consumption is the main urban energy consumption component, which mainly serves people-centered work and living energy demands. Based on the physical requirements of humans in urban buildings and to determine the comfortable body temperature in each season, this paper establishes a sizing optimization model of building-type integrated energy systems (IES), where the cooling and heating loads required to maintain indoor somatosensory body comfortable temperature are calculated. Depending on the external energy price, internal power balance and other constraints, the model develops an optimal sizing and capacity panning method of energy conversion and storage unit in a building-type IES with PV generation. The operating principle is described as follows: the PV generation is fully consumed, a gas engine satisfies the electric and thermal base load requirements, while the power system and a heat pump supply the remaining loads. The gas price, peak-valley electricity price gap and heat-topower ratio of gas engines are considered as important factors for the overall techno-economic analysis. The developed method is applied to optimize the economic performance of building-type IES and verified by practical examples. The results show that using the complementary characteristics of different energy conversion units is important to the overall IES cost.

All solar thermal systems, due to their thermal nature, can be hybridised or operated with both fossil fuel and solar energy. By enhancing availability and dispatch ability, hybridization has the potential to boost the value of concentrating solar thermal technology. Hybrid photovoltaic thermal systems (PV/T) offer a solution to improve on the limited capacity growth seen with standard solar panels. The analysis focuses on the creation of alternative structural and design so-lutions that may be used to boost lacking efficiency that was previously hampered by limited spectrum absorption of sun light. As a result, the spectrum is separated into two spectrum ranges, one that directly matches the bandgap of PV materials and the other that is absorbed for thermal absorption outputs. Most two channel systems are used to capture or reflect sunlight, with the layer specifically located right above the PV cell. Another layer of nanofluid is employed to evacuate heat from the PV cell, acting as the second channel, to specifically eliminate overheating difficulties. To address concerns that have arisen as a result of years of observation, the most recent study involves nano-particle-based fluids employed in PV/T, which uses a cooling medium to provide an alternate heat transfer option. Aside from nanofluids, there are phase change materials, channel alterations that result in a higher flow rate and hence improve overall performance.

In Lubumbashi, the capital of Haut Katanga in the Democratic Republic of the Congo (DR Congo), diesel power plants are a common source of electricity. The need to utilise local renewable energy sources in DR Congo has increased due to the unreliability of the state grid and the rising cost of running Diesel generators. Solar photovoltaic (PV) panels and batteries, in particular, have recently seen significant price drops. Therefore, it is important for operators and suppliers to choose optimal generators together with a renewable energy system to lessen the energy deficit. Diesel generators are still widely used in DRC, but their efficiency pales in contrast to that of more recent power facilities. Consuming fossil fuels results in high expenses for upkeep and operation, in addition to severe environmental damage. This study assessed the feasibility of using local weather and technical data to evaluate the efficiency of a diesel power plant hybridized with a PV system. Hybrid Optimization Model for Electric Renewable (HOMER) simulations suggest that the hybrid system schedule is preferable due to its many economic and environmental advantages for the local community and its inhabitants. The promotion of such a hybrid system, then, may encourage the sustainable economic development of a stable source of electricity for the Congo Region.

This article has been developed to assess the economic feasibility of a roof-top photovoltaic installation of industrial self-consumption. Numerical models that enable an interested person to obtain the main expected parameters will be generated. To do this, a calculation methodology will be generated through which the reader, knowing the location of the facility and dimensions of the roof, will be able to calculate the maximum installable power, the main parameters related to production, the cost of the installation, and the LCOE of the plant. The use of actual costs will be facilitated in case they are known, but it will remain possible to apply the costs of the major equipment (modules, inverter, and structure) considered throughout the article. This developed calculation methodology will also allow a quick comparison of the forecasts of production, CAPEX, and LCOE of plants designed with different inclinations and different types of modules. Consequently, it will be especially useful for decision-making before developing the plant's basic engineering. Moreover, the calculations used for modeling the LCOE will be analyzed in depth. This analysis will allow evaluating how the different technical variables affect the profitability of a photovoltaic installation, such as the selected tilt, the location, the module's technology, or the available area.

The paper addresses an analysis of the efficiency and profitability of the operation of a photovoltaic installation located in the geometric centre of Europe (near Białystok, Poland), where the intensity of solar irradiation is not too high compared to other European countries. It is calculated that in that place average solar irradiation being lower even by approx. 26 kWh than that for the whole Europe, which results in a 26% drop in the economic potential of the utilisation of solar energy for its conversion. A case study and an economic analysis show that without minimum funding amounting to 50% of the investment costs paid for the modernisation of a central heating system assisted by PV cells, the time of return of pecuniary expenditures exceeds 7 years. Apart from the Simple Pay-Back Time SPBT, discount indicators determined in the paper also include the net present value NPV and the internal rate of return IRR. Moreover, a direct ecological effect has been determined for such an investment.

The energy yield of the Vehicle-integrated photovoltaic (VIPV) differs from that of the standard photovoltaics (PV). It is mainly by the difference of the solar irradiance onto the car-roof and car-bodies as well as its curved-shape. Both meaningful and practical modeling and measurement of the solar irradiance for VIPV are needed to be newly established, not the extension of the current technologies. The solar irradiance was modeled by a random distribution of the shading objects and car-orientation with the correction of the curved surface of the PV modules. The measurement of the solar irradiance onto the car-roof and car-body was done using five pyranometers in five local axes on the car for one year. The measured dynamic solar irradiance onto the car-body and car-roof was used for validation of the solar irradiance model in the car.

A car-roof photovoltaic has an enormous potential to change our society. With this technology, 70% of the personal car can run by the solar energy collected by the solar panel on its car-roof. Unfortunately, it is not a simple extension of the conventional photovoltaic technology. This paper list what we need to do for realizing the future that majority of the personal cars run by renewable solar energy, after clarification of the difference from the conventional photovoltaic technology. In addition to the technological development, the standardization of this innovative technology will be important, and the list was made highlighting the standardization.

Sour waters are one of the main aqueous byproducts generated during petroleum refining and require processing in Sour Water Treatment Units (SWTUs) to remove contaminants such as H₂S and NH₃ in compliance with environmental legislations. Therefore, monitoring the composition of SWTU effluents, including acid gas, ammoniacal gas, and treated water, is essential. This study aims to present an AI (artificial intelligence) hybrid-based methodology to develop soft sensors capable of real-time prediction of H₂S and NH₃ mass fractions in the effluents of SWTUs and validate them using real data from industrial units. Initially, a new database based on the dynamic simulation of a two stripping columns SWTU phenomenological model, developed in Aspen Plus Dynamics® V10, was generated, aiming at non-faulty runs, unlike our previous work [1]. Ensemble methods (Decision Trees), such as Gradient Boosting and Random Forest, and Support Vector Machines were compared for soft sensor creation using these simulated data. The best outcome was the development of six soft sensors based on Random Forest with R² greater than 0.87, MAE less than 0.12, MSE less than 0.17, and RMSE less than 0.41. Variable importance analysis revealed that the temperature of the second stage of Column 1 significantly influences the thermodynamic equilibrium of H₂S and NH₃ separation from sour waters, being critical for five of the six soft sensors. After this initial stage using data from the phenomenological model, data from an industrial-scale SWTU were used to develop real soft sensors. The results proved the effectiveness of the conjugated use of physical model and industrial data approach in the development of soft sensor for two-column SWTUs.

The study aimed to know the direct effect of strategic leadership on the quality of service represented by wireless communications services, in addition to knowing the indirect effect of strategic leadership on the quality of service when using performance as an intermediary variable. This research was conducted in government institutions in the Republic of Yemen. Represented by the offices of the Ministry of Communications and Information Technology in five Yemeni cities, it targeted senior management employees, boards of directors, and middle management concerned with strategic planning and strategic leadership. To measure and evaluate the factors of strategic leadership and service quality in Offices of the Yemeni Ministry of Communications Ministry of Communications and Information Technology of the Republic of Yemen. Moreover, performance. A questionnaire was formulated and distributed to the study sample, and data was collected through questionnaires for 150 individuals in some offices of the Yemeni Ministry of Communications. This study uses structural equation model analysis from the Partial Least Squares program through the Smart Plus 4 programs. The study reached a set of results, including that all models show a direct, positive and significant effect of strategic leadership on the quality of service represented by the quality of services in the offices of the Ministry of Communications. As well as the positive relationship between them, as well as the direct and positive impact of performance on the quality of service, as well as the positive and significant relationship between them. While the results indicated a positive and significant indirect effect of strategic leadership on service quality, there is also a positive and significant indirect relationship between strategic leadership on service quality when using performance as an intermediary variable.

This study explores the hydrogen generation potential via water-splitting reactions under UV-vis radiation, by using a synergistic assembly of ZnO nanoparticles integrated with MoS2, single-walled carbon nanotubes (SWNTs), and crystalline silicon nanowires (SiNWs) to create the MoS2-SiNWs-SWNTs@ZnONPs nanocomposites. A comparative analysis of MoS2 synthesized through chemical and physical exfoliation methods revealed that the chemically exfoliated MoS2 exhibited superior performance, thereby being selected for all subsequent measurements. The nanostructured materials demonstrated exceptional surface characteristics, with specific surface areas exceeding 300 m²g⁻¹. Notably, the hydrogen production rate achieved by a composite comprising 5% MoS2, 1.7% SiNWs, and 13.3% SWNTs at an 80% ZnONPs base was approximately 3909 µmol h⁻¹g⁻¹ under 500 nm wavelength radiation, marking a significant improvement of over 40-fold relative to pristine ZnONPs. This enhancement underscores the remarkable photocatalytic efficiency of the composites, maintaining high hydrogen production rates above 1500 µmol h⁻¹g⁻¹ even under radiation wavelengths exceeding 600 nm. Furthermore, the potential of these composites for energy storage and conversion applications, specifically within rechargeable lithium-ion batteries, was investigated. Composites, similar to those utilized for hydrogen production but excluding ZnONPs to address its limited theoretical capacity and electrical conductivity, were developed. The focus was on utilizing MoS2, and SiNWs, and SWNTs, as anode materials for Li-ion batteries. This strategic combination significantly improved the electronic conductivity and mechanical stability of the composite. Specifically, the composite with 56% MoS2, 24% SiNWs and 20% SWNTs offered remarkable cyclic performance with high specific capacitance values, achieving a complete stability of 1000 mA h⁻¹g⁻¹ after 100 cycles at 1 A g⁻¹. These results illuminate the dual utility of the composites, not only as innovative catalysts for hydrogen production but also as advanced materials for energy storage technologies, showcasing their potential in contributing to sustainable energy solutions.

This study explores the use of remote ultrasound vibration to enhance welding strength. It examines the effects of 20 kHz, and 40 kHz High Power Ultrasound Transducers (HPUT) in contact and contactless modes during ultrasonic assistance laser welding. Employing shear tests and microscopy for assessment, the research evaluates ultrasound's impact on welding strength and identifies the optimal transducer. Theoretical and numerical analyses investigate vibration transmission into the welding area, particularly examining the vibration distribution and cavitation initiation within the molten pool area. Results indicate that ultrasound-assisted welding increases pull test performance, including the resistance force and strain, and improves microscopic structural integrity. Numerical simulations suggest that narrow-band vibration intensifies pressure in specific welding zones. Contactless ultrasound application also shows enhanced welding quality, offering a promising alternative to current methods. This work contributes to electric car technology by suggesting improvements in welding techniques for power battery systems.

The reduction of PV prices and interest in energy independence accelerate the adoption of residential battery storage. This storage can support various functions of an energy system undergoing decarbonization. In this work, operative benefits of the storage from the system perspective, namely, generation cost reduction and congestion mitigation, are investigated. Germany is chosen as a case study due to its strong reliance on variable renewable energy. For the analysis, an economic dispatch model with a high spatial resolution is coupled with a Pan-European transmission grid model. It is shown that the system's generation costs are highest when the assets are used only to maximize the PV self-consumption, and the costs are lowest when the storage also reacts to the market dynamics. This amounts to 6% cost reduction. Both operation strategies result in an equal level of grid congestion and infrastructure loading. This is improved with a strategy that accounts regional peak reduction as a secondary objective. The high congestion level emphasizes the grid expansion need to keep pace with the generation and electrification expansion necessary to decarbonize other sectors. Lastly, policymakers should enable multipurpose utilization, e.g., via the introduction of market-oriented retail electricity prices with intervention options for grid operators.

Renewable energy sources are increasingly crucial for meeting global energy demands in an eco-friendly manner, particularly as the world shifts away from fossil fuels and faces higher volatility of the market prices. Portugal, a country with limited fossil fuel reserves and high energy dependency, has heavily invested in renewables in recent years. However, renewables like sunlight, wind, and water are inherently unsteady due to climate influences, resulting in energy production fluctuations. To mitigate this issue, energy storage systems are being deployed to stabilize renewable energy supply during production lulls. This project aims to assess an energy storage system and define technical specification in order to maximize profitability at the Finerge-owned Alto Douro wind farm. To achieve this, we've conducted an energy demand analysis, followed by simulations to assess system performance in relation to energy use and profit, while varying parameters such as power and efficiency. We've also compared commercial proposals from different battery manufacturers utilizing various technologies. Our findings suggest that high-power, quick charge-discharge lithium-ion batteries are the most suitable solution, given their efficiency and modularity. These attributes are vital for achieving current and future profitability.

Silicon has been proved to be one of the most promising anode materials for the next generation of lithium-ion battery. For the application in batteries, Si anode should have high capacity and must be industrially scalable. In this study, we have designed and synthesised a hollow structure to meet these requirements. All the processes are carried out without special equipment. The Si nanoparticles that are commercially available are used as the core sealed inside TiO₂ shell, with rationally designed void space between the particles and shell. The Si@TiO₂ are characterised using X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), and scanning electron microscope (SEM). The optimised hollow structured silicon nanoparticles, when used as anode in lithium-ion battery, exhibit a high reversible specific capacity over 600 mAhg-1. This excellent electrochemical property of the nanoparticles can be attributed to their optimised phase and unique hollow nanostructure.

Two-dimensional MXene synthesized from MAX phase ceramic has the good electrical conductivity, promising to be used as electrodes. In this study, Nb4C3Tx MXene and low-entropy (Nb0.8Ti0.05V0.05Zr0.05Ta0.05)4C3Tx MXene were prepared by etching Nb4AlC3 and (Nb0.8Ti0.05V0.05Zr0.05Ta0.05)4AlC3 ceramics in the HF acid at 60 oC. By investigating the electrochemical properties of lithium batteries, it was found that the Nb4C3Tx and (Nb0.8Ti0.05V0.05Zr0.05Ta0.05)4C3Tx could provide the specific capacities of 163.7 mAh·g-1 and 130 mAh·g-1 after 50 cycles at a current density of 0.1 A·g-1, respectively, and maintain the coulombic efficiency close to 100%, good for the utilization of electrodes in the lithium batteries.

The increased interest in space activities, structural health monitoring, and terrestrial monitoring in hostile and inaccessible zones places a high demand for energy sources for autonomous systems. Conventional electrochemical batteries that could be used are plagued by low energy storage density, short life, disposal of unwanted batteries, and related undesired recharging or replacement maintenance requirements, which endangers the environment. Fuel cells and solar energy sources being exploited to mitigate the adverse effect of environmental threats posed by batteries and fossil fuels are costly to acquire and maintain. The availability of energy sources derived from waste heat from radioactive decay for domestic appliances and industrial equipment will also help alleviate the effects of climate change, which continues to threaten the environment due to fossil fuel energy-based sources that emit harmful carbon monoxide into the atmosphere. A combination of energy from waste heat, harvested via thermoelectricity and existing battery technology to produce a hybrid energy source, can guarantee secured energy for an extended period. Based on the Seebeck effect, thermoelectric energy generation may considerably contribute to sustainable energy development and meet the power demand for spacecraft applications. Modeling of the energy from waste heat, the Li-ion battery, and a hybrid energy source are considered, and their performances are established using the MATLAB/Simulink environment. Results confirmed the comparative advantage of the hybrid energy source over and above the respective electrochemical batteries and waste heat energy sources regarding effectiveness and performance efficiency. Since batteries are required to operate in a constantly changing environment, the effects of temperatures on batteries were investigated. The results show that the performances of batteries decrease with a decrease in ambient temperature and that the higher the maximum operating capacity, the higher the battery's internal temperature.

The novelty of this study consists in: i) synthesis and characterization of electrode materials recycled from a spent car battery and doped with MnO2 and CuO by the analysis of X-ray diffraction (XRD), Infrared (IR) and Electron Paramagnetic Resonance (EPR) data and ii) the investigation of electrochemical properties of prepared materials in view of new applications as electrode materials for battery. Electron Paramagnetic Resonance (EPR) data indicate that the intensity of the resonance line corresponding to the Cu+2 ion was modified with the increase of the dopant content. The analysis of X-ray Absorption Spectroscopy (XAS) data indicates that by increasing the dopant content there is a process of ordering the oxygen atoms around the lead similar to the PbO2 theoretical model. The electrochemical performances of the recycled and manganese-copper-doped materials are optimized for applications as new anodic electrode for the car battery.

The increasing penetration of renewable energy sources in power grids highlights the role of battery energy stor- age systems (BESSs) in enhancing the stability and reliability of electricity. A key challenge with the renewables’, specially the BESSs, integration into the power system is the lack of proper dynamic model for stability analysis. Moreover, a proper control design for the power system is a complicated issue due to its complexity and inter-connectivity. Thus, the application of decentralized control to improve the stability of a large- scale power system is inevitable, especially in distributed energy sources (DERs). This paper presents an optimal distributed hybrid control design for the interconnected systems to suppress the effects of small disturbances in the power system employing utility-scale batteries based on existing battery models. The results show that i) the smart scheduling of the batteries’ output reduces the inter-area oscillations and improves the stability of the power systems; ii) the hybrid model of the battery is more user-friendly compared to the Western electricity coordinating council (WECC) model in power system analysis.

This code provides computational facilities to simulate current versus time during the charging of Li-ion cells at desire constant voltage by considering multiscale physical phenomena. This code only considers a powder of active materials (at microscale or nanoscale) and a small part of electrolyte around it as a half cell. Then it is extended to a complete cell by applying correct boundary conditions. This code is very useful by modifying code parameters to understand the effect of the complex shape of active materials powder (surface area and powder size), kind of electrolyte, and the applied voltages on the charging response of Li-ion cell. As a summary, a microscale approach to the design of Li-ion cells has been provided via this code.

Universitas Sebelas Maret (UNS) through SMART UNS Company has conducted research and development of e-motorcycle conversion using Li-ion battery pack as a substitute for ICE energy source from the conventional motorcycle. Currently, the battery-pack that used for e-motorcycle conversion is in the development phase towards commercialization. The challenge of estimating production costs is the complicated production process and storing hidden expenses that can be a problem. This hidden cost is often a missing or varied factor that costs less or more expensive. This study presents an integrated parametric cost estimation model with activity-based cost assignments to estimate production costs through cost calculations for each activity. Activity-based costs break the production process into a specific cost element for each step. Each activity's cost is put into a parametric cost estimation model to calculate the cost of each activity into the total cost of production. Cost estimation results will be analyzed using a regression method to determine which variables most affect the production cost of Li-ion battery packs for the conversion of e-motorcycles in the SMART UNS company.

LiFePO₄ (LFP) or Lithium-ion battery with its advantages compared to common current motorcycle battery is an appropriate alternative in substituting wet and dry cell battery. Huge amount of demand of motorcycle along with the battery in Indonesia also make it an interesting product for business. In order to assess the commercial potential for such a new technology, market share needs to be estimated as well as the techno-economic feasibility. Hence, market share prediction using the residents of Surakarta Region and techno-economic analysis using NPV, IRR and PBP indicators have been conducted in this study. Calculation using markov chain method shows that LFP battery tends to dominate the market after certain period. Techno-economic analysis also figures out that the commercialization is feasible in three conditions - first mover, even with market leader and equilibrium point. Therefore, there is a great commercial potential for LFP battery especially in Indonesia.

A low-cost bio-mass-derived carbon substrate has been employed to synthesize MoS₂@carbon composites through a hydrothermal method. Carbon fibers derived from natural cotton provide a three-dimensional and open framework for the uniform growth of MoS₂ nanosheets, thus constructing hierarchically coaxial architecture. The unique structure could synergistically benefit fast Li-ion and electron transport from the conductive carbon scaffold and porous MoS₂ nanostructures. As a result, the MoS₂@carbon composites, when served as anodes for Li-ion batteries, exhibit a high reversible specific capacity of 820 mAh g^-1, high-rate capability (457 mAh g^-1 at 2 A g^-1), and excellent cycling stability. The superior electrochemical performance makes the MoS₂@carbon composites to be low-cost and promising anode materials for Li-ion batteries.

A techno-economic model was developed to investigate the influence of components on the system costs of redox flow batteries. Sensitivity analyses were carried out based on a example of a 10 kW/120 kWh vanadium redox flow battery system and the costs of the individual components were analyzed. Particular consideration was given to the influence of material costs and resistances of bipolar plates and energy storage media as well as voltages and electric currents. Based on the developed model it was possible to formulate statements about the targeted optimization of existing battery systems and general aspects for future developments of redox flow batteries.

The current state-of-the-art does not provide a universal and rapid method of determining the state of health (SOH) of a battery or a supercapacitor without carefully examining the degradation of hundreds of full charge/discharge cycles. Lithium-ion batteries, sodium-ion batteries and supercapacitors of different cell chemistries were studied by impedance spectroscopy during lifetime tests. Faradaic and capacitive charge storage are distinguished by the relationships between stored electric charge and capacitance. For batteries, impedance spectroscopy is best applicable in the flat region of the voltage-charge curve. An approximately linear correlation between pseudocapacitance and Ah capacity is observed as long as overcharge and deep discharge are avoided. The correct calculation of quantities related to complex impedance and differential capacitance is outlined – which may also be useful as an introductory text and tutorial for newcomers to the field. Novel diagram types are proposed for the purpose of instant performance and failure diagnosis of batteries and supercapacitors.

This paper presents three approaches to estimating battery parameters of the electrical equivalent circuit model (ECM) based on electrochemical impedance spectroscopy (EIS); these approaches are referred to as (a) least squares (LS), (b) exhaustive search (ES), and (c) nonlinear least squares (NLS). The ES approach is assisted with the LS method for the rough determination of the lower and upper bound of the ECM parameters, and the NLS approach is incorporated with the Monte Carlo run such that different initial guesses can be assigned to improve the goodness of EIS fitting. The proposed approaches are validated using both simulated and real EIS data. Compared to LS approach, the ES and NLS approaches show better fitting accuracy at various noise levels; whereas both in the validation using simulated EIS data and actual EIS data collected from LG 18650 and Molicel 21700 batteries, the NLS approach shows better fitting accuracy than that of LS and ES approaches. In all cases, compared with the ES approach, the computational time of the NLS approach is significantly faster, and compared with the LS approach, the NLS approach shows a minimal difference in computational time and considerably better fitting performance.

In this work, we develop a detailed analysis of the current panorama for electric vehicle charging technology, focusing on the various levels and types of charging protocols and used connectors. We propose a charging station for electric cars powered by solar photovoltaic energy, performing the analysis of the solar resource in the selected location, sizing the photovoltaic power plant to cover the demand completely, and exploring different configurations such as grid connection or physical and virtual electric energy storage. Despite the current development applying for specific working conditions, operating voltage, charging rate, power demand, etc., the proposed configuration is modular, adaptable, and resilient. The simulated system operates within the 360 V to 800 V range of continuous current for charging the electric vehicles, with a selectable power range between 20 and 180 kW. The basic layout includes four charging poles, each servicing all working voltages. An oversized PV plant powers the charging station at any time of the year, saving money compared to the alternative of the electric storage unit. In addition, we build simulation tools and algorithms that optimize the design of future projects, providing a solid basis for sustainable energy infrastructure planning and design.

It is essential to have a thorough knowledge of the genetic variation among different strains of Xanthomonas citri pv. citri (Xcc), which is responsible for causing citrus bacterial canker. This understanding is important for studying the disease’s characteristics, population structure, and evolution, and ultimately for developing sustainable methods of control. A total of 48 strains, obtained from citrus production areas in Burkina Faso in 2012, 2020, and 2021, were subjected to polymerase chain reaction (PCR) tests using specific primers. The aim was to examine the distribution of type 3 effectors (T3E) and determine the geographical origins of the strains. The examination of the distribution of type 3 non-transcription activate like effectors (TALE) indicates a broader range in strains obtained in 2020 and 2021 compared to those obtained in 2012. However, all strains possess a shared set of three genes, specifically XopE2, XopN, and AvrBs2. Furthermore, all examined effectors were observed in the Bobo-Dioulasso region. Regarding the characterization of TALEs, two profiles containing two to three TALEs were discovered. Profile 1, consisting of two TALEs, was found in 37 Xcc strains, whereas Profile 2, comprising three TALEs, was detected in 11 strains. Out of the three TALEs (A, B, and C) that were identified, TALEs B and C were present in all strains. The correlation matrix indicated a positive association between the T3E content of strains and the duration of their isolation. Principal component analysis revealed a limited organization of the strains under investigation

A comprehensive understanding of the genetic diversity among strains of Xanthomonas citri pv. citri (Xcc), the causative agent of citrus bacterial canker, is crucial for unraveling the pathological nature, structure, and evolution of populations, thereby facilitating the adoption of sustainable control measures. In a collection of 48 strains isolated in 2012, 2020, and 2021 from citrus production areas in Burkina Faso, polymerase chain reaction (PCR) tests utilizing specific primers were conducted to investigate the distribution of type 3 effectors (T3E) and the structuring of strains based on their geographical origins. The analysis of the distribution of type 3 non-transcription activate like effectors (TALE) reveals a more extensive repertoire in strains isolated in 2020 and 2021 compared to those isolated in 2012. Nevertheless, all strains share a common repertoire of three genes, namely XopE2, XopN, and AvrBs2. Additionally, all screened effectors were observed in the Bobo-Dioulasso locality. Concerning the characterization of TALEs, two profiles consisting of two to three TALEs were identified. Profile 1, with two TALEs, was present in 37 Xcc strains, while Profile 2, with three TALEs, was identified in 11 strains. Among the three TALEs (A, B, and C) identified, TALEs B and C were common to all strains. The correlation matrix revealed a positive correlation between the T3E content of strains and the years of their isolation. Multiple component analysis indicated a weak structuring of the tested strains.

Solar photovoltaic (PV) generation suffers from multiple serious issues, for example shading effects directly affect the performance of installed PV arrays. By studying these issues, it can play a key role in improving the limitations and performance of PV panels. The study of PV arrays under partial shading conditions is mentioned in many papers as a part of other studies and as an independent phenomenon. Therefore, it is essential to improve these studies and update them with new research and study this problem in detail to know how to limit the effects of partial shading irradiance conditions on PV arrays performances, including economical aspects. This paper proposes to study the effects of different partial shading irradiance conditions for a PV array in various configurations. The analysis is proved in detail through the simulation of the proposed PV array in the Matlab/Simulink environment. The obtained results show the performances of interconnected PV arrays under different partial shading irradiance and temperature conditions, including the solar array I-V and P-V characteristics. In addition, different PV array configurations with and without bypass and blocking protection diodes improve and minimize the effect of partial shading conditions and avoid the reductions in output power.

Taking a socio-technical perspective, I focus on solar businesses (niche market actors) in Iran. As one of the key stakeholder groups whose business prosperity is tied to the development of solar PV, they play a crucial role in accelerating the energy transition. Given the incumbent fossil-based electricity sector in Iran and the least enabling policies, I am first interested to find (i) the main drivers and barriers of solar businesses; and (ii) the roles these solar businesses play in bringing solar PV deployment forward in Iran. I collected the data via 20 semi-structured interviews with solar businesses in Golestan, Guilan, Tehran, Khorasan Razavi, and Eastern Azerbaijan Provinces in Iran. Taking an inductive approach, I considered sustainability transition and social acceptance theories as sensitising concepts to investigate common and specific points of solar business acceptance in Iran. I find ecological awareness, belief in intergenerational justice, and willingness to innovate, as the main intrinsic drivers and socioeconomic opportunity and tackling the energy imbalance as extrinsic drivers; while the lack of a common vision with the energy governors, and the low knowledge of solar PV among the customers, escalating prices, and challenges to accessing good quality solar equipment are the most prior obstacles. Moreover, I understand educating people, driving the innovative deployment of solar PV, and facilitating the diffusion of it, as the major roles of solar businesses in Iran. I find that the sustainability transition literature overlooked the key role of solar businesses specially in fossil-based and developing economies. My findings suggest that the positive intrinsic mechanisms among the solar businesses, in combination with better-enabling policy frameworks and external factors, like lifting the sanctions and joining the global energy market, climate change mitigation commitments and standards, can help solar businesspeople to lead and accelerate solar PV development in Iran.

Load Frequency Control (LFC) is essential to ensure the stability and performance of power systems. In this study, a novel optimization algorithm, the Sea Horse Optimizer (SHO) algorithm, was proposed for optimizing controller parameters in LFC problems of power system. The proposed SHO algorithm was tested on a two-area power system with photovoltaic system and reheat thermal units, under three different scenarios: a 10% load change in both area, large load disturbances, and varying solar radiation. The proposed algorithm optimizes the gain parameters of PI/PID controllers using performance metrics such as Integral of Absolute value of the Error (IAE), Integral of Square Error (ISE), Integral of Time multiplied by Square Error (ITSE), and Integral of Time multiplied by Absolute Error (ITAE). The study compared the performance of the SHO-optimized controller with other reported optimization algorithms such as Genetic Algorithm (GA), Firefly Algorithm (FA), Whale Optimization Algorithm (WOA), and Modified Whale Optimization Algorithm (MWOA). The study also evaluated the accuracy and effectiveness of the controllers using performance metrics such as Settling Time, Overshoot (M+), and Undershoot (M-). The results show that the SHO-tuned controller significantly reduces overshoot, undershoot, and settling time of the system oscillations compared to other algorithms. The study provides valuable insights into the optimization of LFC controllers and presents a significant contribution to the literature with its novel algorithm. The proposed SHO algorithm can be considered an effective alternative solution method for LFC in power systems.

The increased global incidence of myopia requires the establishment of therapeutic approaches. Previous studies have suggested that inflammation plays an important role in the development and progression of myopia. We used human retinal pigment epithelial cell to study the molecular mechanisms on how FJE and PVE lowering the inflammation of the eye. The effect of FJE and PVE in MFD induced hamster model and explore the role of inflammation cytokines in myopia. Expression levels of IL-6, IL-8, and TNF-α were upregulated in retinal pigment epithelium (RPE) cells treated with IL-6 and TNF-α. FJ extract (FJE) + PV extract (PVE) reduced IL-6, IL-8, and TNF-α expression in RPE cells. Furthermore, FJE and PVE inhibited inflammation by attenuating the phosphorylation of protein kinase B (AKT), and nuclear factor kappa-light-chain-enhancer of activated B (NF-κB) pathway. In addition, we report two resveratrol + ursolic acid compounds from FJ and PV and their inhibitory activities against IL-6, IL-8, and TNF-α expression levels in RPE cells treated with IL-6 and TNF-α. FJE, PVE, and FJE + PVE were applied to MFD hamsters and their axial length was measured after 21 days. The axial length showed statistically significant differences between phosphate-buffered saline- and FJE-, PVE-, and FJE + PVE-treated MFD eyes. FJE + PVE suppressed expressions of IL-6, IL-8, and TNF-α. They also inhibited myopia-related transforming growth factor-beta (TGF)-β1, matrix metalloproteinase (MMP)-2, and NF-κB expression while increasing type Ⅰ collagen expression. Overall, these results suggest that FJE + PVE may have a therapeutic effect on myopia and be used as a potential treatment option.

A photovoltaic-thermal (PVT) collector is a solar-based micro-cogeneration system which generates simultaneously heat and power for buildings. The novelty of this paper is to conduct energy and exergy analysis on PVT collector performance under two different European climate conditions. The performance of the PVT collector is compared to a PV panel. Finally, the PVT design is optimized in terms of thermal and electrical exergy efficiencies. The optimized PVT designs are compared to the PV panel performance as well. The main focus is to find out if the PVT is still competitive with the PV panel electrical output, after maximizing its thermal exergy efficiency. The PVT collector is modelled into Matlab/Simulink to evaluate its performance under varying weather conditions. The PV panel is modelled with the CARNOT toolbox library. The optimization is conducted using Matlab gamultiobj-function based on Non-Dominated Sorting Genetic Algorithm-II (NSGA-II). The results indicated 7.7% higher annual energy production in Strasbourg. However, the exergy analysis revealed a better quality of thermal energy in Tampere with 72.9% higher thermal exergy production. The electrical output of the PVT is higher than from the PV during the summer months. The thermal exergy- driven PVT design is still competitive compared to the PV panel electrical output.

In this paper, an extensive study on the operation, control and performance of a hybrid photovoltaic and wind turbine (PV-WT) system is presented. The study includes the operation of the hybrid systems under different weather conditions which are reflected on a change in the wind speed and irradiance. Various loading conditions are investigated such a change in active and reactive power demands for static and dynamic loads. The performance of the hybrid system is examined via MATLAB/SIMULINK simulations.

Nowadays, rotor-stator mixers are widely used in the chemical process industry to carry out the dispersion and de-agglomeration processes for manufacturing the homogenous electrode slurries. Development of the process simulation models for the turbulent mixing of these slurries helps to optimize the mixing parameters such as rotational speed and dispersion time. In this work, computational fluid dynamics (CFD) approach through ANSYS Fluent are explored to determine and analyze the flow patterns, velocity fields and viscosity distribution during the dispersion of anode slurries. It utilizes a non-homogeneous Eulerian multiphase approach and the typical k-ε model to create turbulence fields and compute the mixing rate. This work significantly improves our understanding of the relationship between rotor speed, dispersion time, viscosity distribution, and mixer geometry in rotor-stator mixers.

This study provides a comprehensive analysis of global patent trends in battery recycling, focusing on secondary batteries and related technologies across Korea, China, and the United States. The data, collected from various patent databases, was quantitatively analyzed to identify technology trends and direct future development. The analysis reveals distinct emphases on technologies such as lithium-ion and waste battery recycling, highlighting notable differences in patent activities among key companies and countries. China's large number of patents in battery manufacturing processes contrasts with the USA's focus on electrochemical cell construction and storage systems, while Korea shows significant activity in waste battery technology. The study underscores the competitive landscape and innovation efforts in the battery recycling sector, providing insights into the technological focuses and priorities of each country. It also identifies key challenges, such as the need for consistent innovation and broader geographic coverage in Korea, enhancing patent influence and international presence in China, and ensuring high patent quality and fostering innovation in lagging sectors in the United States. Addressing these challenges through enhanced collaboration, increased R&D investments, and supportive policies is crucial for strengthening the global position and driving further innovation in the battery recycling sector.

Heat dissipation from Li-ion batteries is a potential safety issue for large-scale energy storage applications. Maintaining low and uniform temperature distribution, and low energy consumption of the battery storage is very important. We studied the fluid dynamics and heat transfer phenomena of a single cell, 16-cell modules, battery packs, and cabinet through computer simulations and experimental measurements. The results show that the temperature distribution of single cell is relatively uniform when the cell is facing the air flow. In a module, very high air flow rate and large gap between the cells can reduce the cell temperature. A pack with a good thermally conductive case is very important to ensure good heat dissipation of the battery module. Due to limited space in the cabinet, additional air inlets and outlets can be opened outside of the cabinet to slightly lower the pack temperature. Installing fins outside the cabinet can also slightly reduce the temperature inside the cabinet. Liquid cooling medium, such as water, is much better than the air-cooling medium.

Electrochemical Impedance Spectroscopy techniques were applied in this work to 9 lead-acid battery prototypes fabricated industrially, divided on three type/technology packages. Frequency dependent impedance changes were interpreted during successive charge/discharge cycles on two distinct stages: 1) immediately after fabrication; and 2) after a controlled aging procedure to 50% Depth of Discharge, following industrial standards. By investigating their State of Health behaviour vs electrical response, three methods were employed, namely the (Q-Q0) total charge analysis, the decay values of Constant Phase Element in the equivalent Randles circuits, and the resonance frequency of the circuit. A direct correlation has been found for prediction of the best performant batteries in each package, thus allowing a qualitative analysis capable to provide the decay of the battery State of Health. We emphasized which parameters are directly connected with their lifetime performance in both stages, and by consequence, which type/technology battery prototype emphasize the best performance. Based on this methodology, the industrial producers can further establish the quality of the novel batteries in terms of performance vs lifespan, allowing them to validate the novel technological innovations implemented in the current prototypes.

This paper investigates the polarization and heat generation characteristics of batteries under different ambient temperatures and discharge rates by means of using a coupled electric-thermal model. The study found that the largest percentage of polarization is ohmic polarization, followed by concentration polarization and electrochemical polarization. The values of the three types of polarization are generally small and stable under normal-temperature environments and low-discharge rates. However, they increase significantly in low-temperature environments and high-discharge rates and continue to rise during the discharge process. Additionally, ohmic heat generation and polarization generation also increase significantly under these conditions. Reversible entropy heat is less sensitive to ambient temperature but increases significantly with the increase of the discharge rate. Ohmic heat generation and polarization heat generation contribute to the total heat generation of the battery at any ambient temperature, while reversible entropy heat only contributes to the total heat generation of the battery at the end of discharge.

Battery Management System helps to improve the transient performance and life of electro-chemical rechargeable batteries like a Li-ion, lead–acid, etc. The investigation here was focused on the crucial part of the Battery Management System that is, Cell balancing, State of charge of the battery, etc. By analyzing the different control strategies a new optimal control strategy is developed to improve the battery performance according to application. The Control strategy is developed using an active and passive cell balancing model with the help of AVL Cruise and MATLAB/SIMULINK software. For the active cell balancing technique, a switched capacitor technique is chosen. To have longer battery life, the time required for the cell balancing must be as low as possible for which many control logics have been defined. The effect of these cell balancing techniques on the performance of battery packs is investigated and it is observed to produce a promising result.

This paper proposes a new battery balancing control strategy based on state of charge (SOC) for addressing the problem of cell-to-cell differences in lithium-ion battery systems. The strategy utilizes a reconfigurable converter system to transfer energy from high-SOC battery modules to low-SOC battery modules and allows balancing the battery modules while they are powering the load. A MATLAB/Simulink simulation model with five batteries was built to validate the effectiveness of the proposed balancing strategy under unloaded and loaded conditions. The simulation results demonstrate that the proposed strategy achieves more efficient and accurate battery module balancing compared to the previous balancing modes, thus increasing the overall lifespan and safety of the battery pack.

Electric Vehicles (EVs) are the need of the hour due to growing climate change problems linked with the transportation sector. Battery Thermal Management System (BTMS), which is accountable for certifying safety and performance of lithium-ion batteries (LiB), is the most vital part of an EV. LiB has auspicious gravimetric energy density but the heat generation due to chemical reactions inside a LiB during charging and discharging causes temperature rise which has a direct effect on LiB performance and safety. This study specifically focuses on aircooled BTMS, defines different types of air-cooled BTMS (active and Passive), discusses limitations associated with air-cooled BTMS, and investigates different optimization techniques and parameters to improve performance of air-cooled BTMS. Maintaining temperature within optimum range and uniform temperature distribution between cells of a battery pack are the major design parameters for improving the performance and efficiency of air-cooled BTMS. Various optimization techniques including cell arrangement with a battery pack, air-flow channel optimization, and air inlet/outlet position variations are discussed and each technique is thoroughly reviewed. Finally, it’s noted that passive air-cooled BTMS is not that effective for long-distance vehicles so most researchers shifted their focus toward active air-cooled BTMS. Active air-cooled BTMS requires a lot of power for effective performance. Lastly, the most recent field of air-cooled BTMS technology which is Air-Hybrid BTMS is discussed and declared a very promising solution for overcoming major limitations associated with air-cooled BTMS.

With a relatively small population, Russia accesses huge oil, natural gas, coal and uranium resources, and hosts advanced nuclear energy, oil and natural gas industries. However, the combined effect of today’s low cost electricity generation via photovoltaic modules, water and wind turbines and similarly low cost storage in Li-ion battery and solar hydrogen obtained via water electrolysis will have a profound impact on Russia’s energy and automotive industries.

Sodium substitution Li1-xNaxMn2O4 cathodes were synthesized by a solid-state reaction method. The morphologies and crystal structures of Li1-xNaxMn2O4 were characterized by scanning electron microscopy (SEM) and X-ray diffraction (XRD), respectively. All Li1-xNaxMn2O4 samples exhibited a single phase LiMn2O4 spinel structure with good crystallinity. The effect of Na+ ions on the electrochemical performance of Li1-xNaxMn2O4 was investigated by galvanostatic charge-discharge test. The results showed that lithium substituted by sodium deteriorated its capacity retention but enhance its discharge capacity when it worked at large current densities. The initial discharge capacity was 114.2 mAh/g for Li0.94Na0.06Mn2O4, and 93.1 mAh/g remained after 300 cycles at a current density of 2220 mA/g in the voltage range 3.0–4.3 V at room temperature.

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.

The article studies and analyzes a hybrid power source system, lithium battery, and fuel cell assisted by flexible photovoltaic panels for hybrid electric vehicles (HEVs). The new configuration operates based on optimizing the performance of the dual power source to maximize the available energy and operating time. The operational mode simulates specific driving conditions in urban, peripheral, and intercity routes under variable driving patterns and traffic conditions. The simulation results show that the new configuration increases the hybrid electric vehicle performance, providing higher reliability despite the more complex design. The proposed system reduces the external power supply dependence and avoids unexpected sudden stops due to energy exhaustion. The new configuration also extends the vehicle driving range depending on driving mode and route conditions. The vehicle driving range extension may reach up to 276.3 km. The hybridization of fuel cells with lithium battery and PV panel assistance enhances battery management, reducing battery servicing and increasing lifespan. The proposed topology is cheaper than a single fuel cell power system by 17.2%, reducing the total cost related to the single battery power system if we consider the battery recharge for its entire lifespan. The cost saving is 2.6% for the American market and 14.8% for the European one.

In the context of energy conversion from renewable sources to distribution grids (insulated or not), a converter is often required to transfer energy from a low voltage source, towards three-phase grids. This paper presents the HW design, the simulation results and the conversion performance of a CSI converter intended to interface low voltages renevable sources to three-phase grids. The main focus of this paper is to obtain the best performance in terms of voltage increase towards the output stage while maximizing the conversion efficiency. In comparison with the currently used energy conversion systems for small photovoltaic systems, hereafter some solutions were adopted to level and maximize the energy flow from the source to the DC-link and improve the quality of current supplied in terms of harmonic distortion. The proposed system is composed of two conversion stages: the first, voltage-to-current, the second current-to-current via a three-phase CSI bridge modulated with SVM technique. The stages are not completely decoupled from an electrical point of view, therefore, in order to mitigate the effects of these interactions, synchronization strategies have been adopted.

This paper offers a theoretical and experimental examination of the concurrent production of electricity and heat using photovoltaic thermal (PV/T) technology. The efficiency performance of the PV/T system is meticulously analyzed using MATLAB/Simulink software environments. Notably, the proposed PV/T system shows reliable performance, and its validity is confirmed through experimental validation on a test stand with a single PV/T panel positioned at a 45-degree angle to the horizontal and a 0-degree azimuth angle.

This paper reports modelling outcomes for improvements to building energy performance in Indonesia. Long-term climate effects due to building energy demands including carbon emissions are also considered. The global change assessment model (GCAM) was used to generate the related end-user building energy data, including socioeconomics for urban areas of Indonesia. As a comprehensive study, the total life cycle of carbon in the building sector and the concept of zero-carbon buildings, including energy efficiency, zero-emissions electricity and fuel switching options were considered. Building shell conductance (u-value) of building envelope, floor area ratio (FAR), air conditioner (AC) efficiency, electrical appliances (APLs) efficiency, rooftop photovoltaic (PV) performance and ground source heat pump (GSHP) systems were considered as parameters to mitigate carbon emissions under the operational energy category in GCAM. Carbon mitigation associated with the cement production process was considered in the raw material category. Urban population and labour productivity in Indonesia were used as base inputs with projected growth rates to 2050 determined from available literature. Low growth rate ‘LowRate’ and high growth rate ‘HighRate’ were considered as variable inputs for u-value, FAR, AC efficiency, APLs efficiency, and PV capacity factor to model emissions mitigation. The energy consumption of the GSHP was compared to the conventional reverse cycle ACs to identify the potential of the GSHP as a fuel-switching option. Only base input data were used for cement production process parameters without applying any variable inputs. GCAM base scenarios based on input data only (without modifying variable data) for the residential building sector in Indonesia were considered the benchmark for this study. Total potential carbon emissions mitigation was found to be 432 Mt CO2-e for the residential building sector in Indonesia over 2020-2050. It was found that an average of 24% carbon emissions mitigation could be achieved by 2020-30 and 76% in 2031-2050.

The requirement for integration of power plants due to the cyclical rise in electrical energy consumption is due to fluctuating load demand with the current grid systems. This integration necessitates effective allocating loads to the power plants for a minimum grid-tied transmission line cost while meeting network constraints. In this paper, we formulate an optimisation problem of minimising the total operational cost of all committed plants transmitted to the grid while meeting network constraints and ensuring economic power dispatch (EPD) and energy management system co-optimization. The developed Particle Swarm Optimization (PSO) method resolve the optimisation problem using piecewise quadratic function to describe the operational cost of the generation units, and the B coefficient approach is employed to estimate the transmission losses. Intelligent adjustments are made to the acceleration coefficients, and a brand-new algorithm is suggested for distributing the initial power values to the generation units. The developed economic power dispatch strategy successfully demonstrated an imperative cost reduction with connected load of 850MW, 1263MW and 2630MW power demand are contrasted with previous PSO application cost values, maximum yearly cost savings of (0.55%, 91.87), (46.55%, 3.78), (73.86%, 89.10) respectively, and significant environmental-benefit. The proposed co-optimisation approach can enhance a significant self-consumption ratio compared to the baseline method.

Microgrid is one of the important ways to accommodate distributed PV generation. However, the optimal planning scheme of microgrids is closely related to solar resources, load characteristics, and the key components of microgrid systems. This paper uses HOMER software to conduct collaborative planning for grid-connected PV-storage microgrids with electric vehicles in multiple scenarios. Specifically, we construct a multi-scenario capacity optimization model for PV generation, energy storage, and converters, considering both the cleanliness and economic performance of microgrids. The performance is quantified using indices such as net present cost, levelized cost of electricity, and carbon dioxide emission under multiple scenarios. Finally, we conduct extensive case studies on a business park in Wuhan, China, to compare and discuss the planning performance under multiple scenarios, as well as sensitivity analysis with specific cases.

This paper shares some new information on the ambient temperature profile and the heat stress occurrences directly underneath ground-mounted Solar Photovoltaic (PV) Arrays (monocrystalline-based) focusing on different temperature levels. A common ground for this work lies on the fact that 10C increase of PV cell temperature results in reduction of 0.5% energy conversion efficiency thus any means of natural cooling mechanism would gain much benefit especially to the Solar Farm operators. Transpiration process plays an important role in the cooling of green plants where in average it could dissipate around 32.9% of the total solar energy absorbed by the leaf making it a good natural cooling mechanism. This condition is relatively applied for herbs specifically for this project, Orthosiphon Stamineus or generally known as Java Tea are used as the high value crops. The thermal process via convective heat and mass exchange of leaves with the environment is relevant for a better understanding of plant physiological processes in response to environmental conversion factors for a wide range of applications. An important fact for plant heat stress with respect to the Ambient temperature is that the range lies between 10 C to 15 C above the surrounding value. This heat stress condition is relatively important and should be modelled in crops-energy integration. Agrivoltaic concept is a system that combines commercial agriculture and photovoltaic electricity generation in the same space. The concept is in line with the Kyoto Protocol and the United Nation Sustainable Development Goals (UN-SDG) which highlights the clean energy and sustainable urban living. The integration of agrivoltaic systems would optimize the yield, improving clean system efficiency and solving the issue of land resource sustainability. The PV bottom surface temperature are the main source of dissipated heat as shown in the thermal images recorded at 5 minutes interval at 3 sampling time. Statistical analysis shows that the Thermal correlations for transpiration process and heat stress occurrences between PV bottom surface and plant height will be an important finding for large scale plant cultivation in agrivoltaic farms.

Solid-state batteries (SSBs) hold the potential to revolutionize energy storage systems by offering enhanced safety, higher energy density, and longer life cycles compared with conventional lithium-ion batteries. However, the widespread adoption of SSBs faces significant challenges, including low charge mobility, high internal resistance, mechanical degradation, and the use of unsustainable materials. These technical and manufacturing hurdles have hindered the large-scale commercialization of SSBs, which are crucial for applications such as electric vehicles, portable electronics, and renewable energy storage. This paper provides a systematic review and cross-sectional bibliometric and thematic analysis of the global patent landscape for SSB technologies. The study classifies innovations into key problem and solution areas by meticulously examining 244 patents across multiple dimensions, including geographic distribution, inventor engagement, award latency, and technological focus. Key findings reveal progress in addressing performance, safety, material sustainability, and manufacturing scalability, with significant innovations in electrolyte, electrode, architectural, and process engineering. This research contributes a comprehensive analysis of the technological landscape, offering valuable insights into ongoing advancements and providing a roadmap for future research and development. This work will benefit researchers, industry professionals, and policymakers by highlighting the most promising areas for innovation, thereby accelerating the commercialization of SSBs, and supporting the transition toward more sustainable and efficient energy storage solutions.

Estimation of core and surface temperature is one of the crucial functionalities of the lithium-ion Battery Management System (BMS) towards providing effective thermal management, fault detection and operational safety. While, it is impractical to measure core temperature using physical sensors, implementing a complex estimation strategy in on-board low-cost BMS is challenging due to high computational cost and the cost of implementation. Typically, a temperature estimation scheme consists of a heat generation model and a heat transfer model. Several researchers have already proposed ranges of thermal models having different levels of accuracy and complexity. Broadly, there are first-order and second-order heat capacitor-resistor-based thermal models of lithium-ion batteries (LIBs) for core and surface temperature estimation. This paper deals with a detailed comparative study between these two models using extensive laboratory test data and simulation study to access suitability in online prediction and onboard BMS. The aim is to guide whether it’s worth investing towards developing a second-order model instead of a first-order model with respect to prediction accuracy considering modelling complexity, experiments required and the computational cost. Both the thermal models along with the parameter estimation scheme are modelled and simulated using MATLAB/Simulink environment. Models are validated using laboratory test data of a cylindrical 18650 LIB cell. Further, a Kalman Filter with appropriate process and measurement noise levels are used to estimate the core temperature in terms of measured surface and ambient temperatures. Results from the first-order model and second-order models are analyzed for comparison purposes.

Global warming and CO₂ emissions have become increasingly pressing concerns, with the aviation industry contributing significantly to these issues. In response, efforts have been made to develop environmentally sustainable aviation solutions. This paper examines the Direct Operating Costs (DOC) of the Wright Spirit, one of the options for electric flight, compared to the conventional BAe 146 on which the Wright Spirit is based. Utilizing methodologies adapted from previous studies (largely the AEA method), the analysis investigates various factors influencing DOC, including battery prices, flight duration, and charging time. Results indicate a 73% increase in overall DOC from the BAe 146 to the Wright Spirit, largely influenced by battery costs and lifespan. However, an 83% reduction in fuel/energy costs suggests the potential viability of the Wright Spirit, particularly with anticipated reductions in battery prices. For instance, a quartering of battery prices could result in a £5 increase in costs for 1-hour flights, compared to the BAe 146. Moreover, the analysis finds the battery lifespan and charging time to be the most important factors to control, in order to increase commercial feasibility. Ticket price comparisons suggest that the Wright Spirit's costs align closely with current market prices, with a flight from Paris to Heathrow predicted to cost the airline £136.10 per passenger. Future research could explore alternative electric aircraft designs, to further assess their impact on DOC and ticket prices.

This work simulates the performance of lithium batteries for electric vehicles under different charge and discharge rates. The simulation is based on similarity factors for power, voltage and current, reproducing the real operation conditions of an electric vehicle at the model scale. Most current driving modes have been analysed corresponding to discharge rates from 0.1C to 0.37C. The simulation has also been applied to determine charging time using charge power in real conditions, from 6.1 kW to 18.3 kW (0.1 C to 0.3C). Driving conditions are obtained using equations for vehicle motion including all forces. Tests have been run under two configurations, continuous and alternate current circuits, to reproduce the two types of engines that electric vehicles use. The simulation shows very good agreement in charge and discharge processes, average deviation of 3% related to real conditions, and 1.6% between them, which proves the validity of the simulation process.

Quasi-solid composited electrolytes were produced by LiFSI initiated polymerized poly-(Dioxolane) (PDOL) with garnet-LLZO (Li7La2Zr3O12) nanofibers and used in lithium-metal batteries. Linear sweep voltammetry shows that the initial oxidation voltage of 4.6 V for Gel-10% (G10, 10% wt. LLZO in PDOL) vs Li/Li+. EIS test of stainless steel// stainless steel symmetric cells for Gel-1% (G1), Gel-5% (G5) and Gel-10% (G10) show ion conductivity (5*10-5 S/cm). Li/G10/Li symmetric cells have stable stripping-plating cycling performance over 1300 hours continuously with the current density of 0.1 mA/cm2 at 25 oC, indicating a good interface contact and stable lithium-ion transport pathway through the composite electrolytes. LFP/G10/Li batteries have stable charge-discharge plateau, low polarization voltage of 0.07-volt, energy efficiency of 95% and coulombic efficiency of ~99% at current density of 26.3 mA/g at 25 oC for over 100 cycles.

This article examines the evolution of the most extensively researched subjects in E-mobility during the previous two decades. The objective of this analysis is to identify the lessons that the State of Kuwait, which is falling behind other nations in E-mobility, can absorb in its efforts to embrace adoptions of electric vehicles (EVs). To strengthen the body of knowledge and deter-mine the most effective and efficient route to an "EV-ready" nation, the authors compiled data on the latest developments in the EV industry. A bibliometric analysis was performed on 3,962 articles utilizing the VOSviewer software, which identified six noteworthy clusters that warranted further attention. Additionally, we examine the sequential progression of these clusters as follows: 1. The environmental ramifications of electric mobility; 2. Advancements in electric vehicle technology, including range extension and soundless engines; and capital (CAPEX) and operational (OPEX) expenditures of purchasing and operating EVs. 3. Concerns regarding effectiveness and durability of EV batteries, 4. Availability of EV charging stations and grid integration, 5. Charging time, and finally 6. Origin and source of the energy utilized in the development of e-mobility. We are of the opinion that by delineating the critical aspects of e-mobility development, policymakers and decision-makers in Kuwait will be better equipped to formulate timely and economical choices pertaining to sustainable transportation.

Significant efforts are being made across academia and industry to better characterize lithium-ion battery cells as reliance on the technology for applications ranging from green energy storage to electric mobility increases. The measurement of short-term and long-term volume expansion in lithium-ion battery cells is relevant for several reasons. For instance, it provides information about the quality and homogeneity of battery cells during charge and discharge cycles, as well as aging over it’s lifetime. The expansion measurements are useful for the evaluation of new materials and the improvement of end-of-line quality tests during cell production. These measurements may also indicate the safety of battery cells by aiding in predicting state of charge and state of health over the lifetime of the cell. Expansion measurements can also assess inhomogeneities on the electrodes and defects such as gas accumulation and lithium plating. In this review, we first establish the known mechanisms through which short term and long term volume expansion in lithium-ion battery cells occurs. We then explore the current state-of-the-art for both contact and non-contact measurements of volume expansion. This review compiles existing literature to outline the various options available to researchers aiming to make ex situ volume expansion measurements by doing post mortem analyses on individual components and in operando measurements on entire battery cells. Finally, we discuss the different considerations when selecting an appropriate measurement technique. The selection of the optimal method for measuring battery cell expansion depends on the objective of the characterization, duration, required resolution, and repeatability of results. Costs and required space for the measurement equipment are also considered.

Decarbonization of air mobility requires the decarbonization of its energy. While biofuels will play an important role, other low carbon energy carriers based on electricity are considered: battery electrification, liquid hydrogen (LH₂) or eFuel, a hydrogen-based energy carrier. Each energy carrier has its own conversion steps and losses and its own integration effects with the aircraft. These combinations lead to different energy requirements and must be understood to compare their cost and CO₂ emissions. Since they are all electricity-based, this study compares these energy carriers using the well to rotor methodology when applied to a standard Vertical Take-Off and Landing (VTOL) air mobility mission. This novel approach allows one to understand that the choice of the energy carrier dictates the propulsive system architecture, leading to integration effects with the aircraft which can significantly change the energy required, from 400 to 2665 kWh for the same mission. These deviations lead significant differences in CO₂ emissions and costs. Battery electrification is impacted by the battery manufacturing but has the lowest electricity consumption. It is an optimum solution but only until the battery weight can be lifted. In all scenarios eFuel is more efficient than LH₂. We conclude that carrying the most efficient molecule in an aircraft pays the extra energy cost spent on the ground. Finally, we found that for each of these energy carriers, it is the electricity carbon intensity and price which will dictate the cost and CO₂ emissions of an air mobility mission.

The EU has planned the phase-out of new vehicles based on internal combustion engines in favour of high efficiency electric cars by 2035 (Fit for 55 package). However, many doubts remain about the effectiveness of this choice for each Country of the Union in terms of CO2 emissions reduction, as each State is characterized by a different carbon intensity related to the production of electricity needed to manufacture and recharge vehicles. This study seeks to explore the Italian case. To this aim, carbon intensities related to the electricity production were calculated considering both the Italian electricity mix production at 2021 and those at 2035, envisaged considering two scenarios based on different introductions of renewable sources (RES). Afterwards, the values obtained were adopted for determining the CO2 emissions related to the whole production process of battery systems in Italy (emissions from mining and refining, scrap materials and final assembly included) by comparing some of the most up-to-date Life-Cycle Assessment (LCA) analysis related to the manufacturing cycle of the batteries. Finally, the results were adopted to calculate the starting carbon debit for A, B, C and M car segments for Mild Hybrid, Full Hybrid and Full Electric powertrains. At the same time, statistical road fuel/electricity consumption data were collected and overall CO2 emissions were calculated for the same vehicles for a defined mileage, so to determine break-even points with respect to the cumulative (i.e., from battery and road) carbon emissions. The results showed that advantages related to electric vehicles are significant only if a low carbon intensity related to electricity production is reached by means of a very high introduction of RES, thus keeping the door open for innovative powertrain technologies (plug-in), if fed with low carbon fuels.

Lithium-ion batteries (LIBs) have become indispensable energy storage devices for various applications, ranging from portable electronics to electric vehicles and renewable energy systems. The performance and reliability of LIBs depend on several key components, including the electrodes, separators, and electrolytes. Among these, the choice of binder materials for the electrodes plays a critical role in determining the overall performance and durability of LIBs. This review introduces polymer binders that have been traditionally used in the cathode, anode, and separator materials of LIBs. Furthermore, it explores the problems identified in traditional polymer binders and examines the research trends in next-generation polymer binder materials for lithium-ion battery as alternatives.

Taking advantage of fact that the surface electrons of metallic nanoparticles (NPs) can be effectively released even at a low voltage bias, we demonstrate an improvement in the electrochemical performance of nano-sized Prussian Blue (PB) based secondary batteries by the incorporation of bare Ag or Ni NPs onto the vicinity of the working PB NPs. It is found that the capacity for electrochemical energy storage of the 17-nm-PB-based battery is significantly higher than the capacity of 10-nm-PB-based, 35-nm-PB-based or 46-nm-PB-based batteries. There is a critical PB size for the highest electrochemical energy storage efficiency. The full specific capacity CF of the 17-nm-PB-based battery stabilized to 62 mAh/g after 130 charge-discharge cycles at a working current of IW = 0.03 mA. The addition of 14 mass-percent of Ag NPs in the vicinity of the PB NPs gives rise to a 32% increase in the stabilized CF. A 42% increase in the stabilized CF can be obtained with the addition of 14 mass-percent of Ag NPs on the working electrode of the 35-nm-PB-based battery. An enhancement of CF is also found for electrodes incorporating bare Ni NPs but the effect is smaller.

The paper concludes that the choice of charging strategy depends on the specific requirements and limitations of the off-grid solar PV system, and that a careful analysis of the factors that affect performance is necessary to identify the most appropriate approach. Also provides valuable insights for designing and optimizing off-grid solar PV systems, which can help to improve the efficiency, reliability, and cost-effectiveness of these systems.

Thermal safety of lithium-ion traction batteries is a highly concerned issue in the field of electric transportation. The large amount of gas emission during the thermal runaway process of batteries has highly safety hazards such as fire and explosion. Quantitative analysis of emission is one of the important challenges for testing and evaluating battery safety. Focus on quantifying the gas emission through large-scale thermal propagation in battery modules and packs, based on the idea of cell result multiplication, this article conducts thermal runaway emission analysis on single cell and modules, and compares the behavior of thermal runaway and gas emission of the cell and module from the aspects of temperature, pressure, gas composition and battery morphology. The feasibility of the cell result multiplication method was verified from the perspective of experimental data.

All-solid-state lithium batteries (ASSLBs) using argyrodite electrolyte materials have shown promise for applications in electric vehicles (EVs). However, understanding the effects of pro-cessing parameters on the ionic conductivity of these electrolytes is crucial for optimizing battery performance and manufacturing methods. This study investigates the influence of electrolyte op-erating temperature, electrolyte operating pressure, electrolyte pelletization pressure, and electro-lyte pelletizing temperature on the ionic conductivity of Li6PS5Cl0.5Br0.5 argyrodite electrolyte (AmpceraTM, D50=10 µm). A specially designed test cell is employed for the experimental meas-urements, allowing for controlled pelletization and testing within the same tooling. The results demonstrate the significant impact of the four parameters on the ionic conductivity of the argy-rodite electrolyte. The electrolyte operating temperature has a more pronounced effect than oper-ating pressure, and pelletizing temperature exerts a greater influence than pelletizing pressure. This study provides graphs that aid in understanding the interplay between these parameters and achieving desired conductivity values. It also establishes a baseline for the maximum pelletizing temperature before undesirable degradation of electrolyte occurs. By manipulating the pelletizing pressure, operating pressure, and pelletizing temperature, battery engineers can achieve the desired conductivity for specific applications. The findings emphasize the need to consider operating conditions to ensure satisfactory low-temperature performance, particularly for EVs. Overall, this study provides valuable insights into processing and operating conditions for ASSLBs utilizing Li6PS5Cl0.5Br0.5 argyrodite electrolyte.

This paper presents an improved SOC estimation method for lithium ion batteries in Electric Vehicles using Bayesian optimized feedforward network. This innovative bayesian optimized neural network method attempts to minimize a scalar objective function by extracting hyperpa-rameters (hidden neurons in both layers) using a surrogate model. Furthemore, the hyperparameters are built and data samples are trained and validated. The performance of the proposed deep learning neural network is evaluated. Two reasonable size data samples are ex-tracted from Panasonic 18650PF Li-ion Mendeley datasets that are used for training and valida-tion. RNN and LSTM neural network algorithms offer the common core property of retaining past information and/or hidden states for better SOC estimation. However, the feature of this pro-posed method is the inclusion of Bayesian optimization that chooses optimal double layer hidden neurons. Analysis of results shows that Bayesian optimized feedforward algorithm with average MAPE (0.20%) is the lowest and is the best selection compared with average MAPE for other five deep learning algorithms. In the last quarter of fuel gauge, where fuel anxiety is severe, feed-forward with Bayesian Optimization algorithm is still the best selection (with MAPE of 0.64%).

To mitigate lithium dissolution and polysulfide shuttle effect phenomena in high energy lithium sulfur batteries (LISBs), a conductive, flexible, and easily modified polymer composite layer was applied on the anode. The polymer composite layer includes polyaniline and functionalized graphite. The electrochemical behavior of LISBs was studied by galvanostatic charge/discharge tests from 1.7 to 2.8 V up to 90 cycles and via COMSOL Multiphysics simulation software. No apparent overcharge occurred during the charge state, which suggests that the shuttle effect of polysulfides was effectively prevented. The COMSOL Multiphysics simulation provides a venue for optimal prediction of the ideal concentration and properties of the polymer composite layer to be used in the LISBs. The testing and simulation results determined that the polymer composite layer diminished the amount of lithium polysulfide species and decreased the amount of dissolved lithium ions in the LISBs. In addition, the charge/discharge rate of up to 2.0 C with a cycle life of 90 cycles was achieved. The knowledge acquired in this study was important not only for the design of efficient new electrode materials, but also for understanding the effect of the polymer composite layer on the electrochemical cycle stability.

As one of the critical state parameters of the battery management system, lithium battery state of charge (SOC) can provide an essential reference for battery safety management, charge/discharge control, and energy management of electric vehicles. To analyze the application of deep learning in electric vehicle power battery SOC estimation, this study reviewed the technical process, common public datasets, and the neural networks used, structural characteristics, advantages and disadvantages of lithium battery SOC estimation in deep learning method. First, the specific technical processes of the deep learning method for SOC estimation were analyzed, including data collection, data preprocessing, feature engineering, model training, and model evaluation. Secondly, the current commonly and publicly used lithium battery dataset was summarized. Then, the input variables, data sets, errors, and advantages and disadvantages of four types of deep learning methods, were concluded using the structure of neural network used for training as the classification criterion. Finally, the challenges and future development directions of lithium battery SOC estimation in deep learning method were explained.

Abstract Women victims of abuse can suffer neuropsychological sequelae that affect memory and attention, as well psychopathological disorders such as depression. These consequences affect their daily life and physical and psychological health. Objective: To analyze sequelae that affect attention and memory, as well a possible association of these sequelae to depression. Method: A total of 68 women victims of gender-based violence participated in the study. The participants were between 15 and 62 years of age and resided in Spain at the time of data collection. The Luria DNA Battery (Neuropsychological Diagnosis of Adults) by Manga and Ramos (2000); and the Beck Depression Inventory were applied. Results: Women victims of gender-based violence suffer neuropsychological sequelae, presenting low short-term memory and attentional control; and score low on the Luria-DNA battery. Of these women, 60% suffer from some relevant type of depression, and there are significant differences according to their degree of memory. Through the HJ-Biplot, a direct relationship was found between memory and attentional control with the total score of the Luria battery. On the other hand, an inverse relationship was found between short-term memory and depression. Lastly, three well-differentiated gender clusters of women victims of gender-based violence were identified. Conclusions: A lower rate of depression is observed in women victims of abuse when they have a more intact short-term memory.

The corrected mechanism model of battery voltammetric function is helpful to guide the development and application of battery. There are two scientific issues that need to be answered: First, how many mechanisms do batteries have; Second, how to establish the mechanism model separately under the overlapping of these mechanisms. Volt-ampere characteristics of both linear state and nonlinear state exist; the monotonic decreasing of volt-ampere characteristics indicates that the battery have only three kinds of mechanisms. Without changing the basic form of the function and under the principle of the mechanism function’s working region considered, we propose a mechanism function which satisfies the monotonic decreasing characteristic of the voltammetric curve of battery, via the derivative law of each mechanism function in the voltammetric function of battery. By using the voltammetric data, the obtained cell mechanism function can accurately predict the potential (current or voltage) when the independent variable of the cell is zero, and provide the theoretical basis for the internal working mechanism of the cell, which can guide the practice.

Lead Acid Batteries (LABs) are used for starting, lighting, and igniting, as well as in air conditioning systems and to supply power to electric engines in transport vehicles (TVs). However, the application of LABs for TVs has faced a number of market challenges, mounted by the upcoming high energy density and long lifespan batteries, such as lithium ion. LABs, on the other hand, are inexpensive. The key research question is, how can the lifespan of LABs used in automotive industries be increased, while still ensuring a low cost solution? Thus, integrating LABs with the supercapacitor (known as an electric double layer capacitor—EDLC) is likely to outperform the competing alternative batteries for TVs. This paper proposes a multiple stage approach to hybrid lead acid batteries and a supercapacitor system for TVs that is capable of maintaining the battery state-of-charge (SOC) at statistically high limits, ranging between 90% and 95%. This SOC target will likely ensure that the lifespan of the hybrid battery system can be elongated (extended) more than its competitors. In this study, the multiple stage approach of concatenated converters has been designed in order to satisfy all energy storage requirements for different characteristics of LABs and the supercapacitor. The designed hybrid system has been simulated using Matrix Laboratory (MATLAB/Simulink (version R2016a, MathWorks, Natick, MA, USA)). The simulated results show that high transient currents from the direct current (DC) bus of LABs, caused by the regenerative braking or deceleration of the TVs, reduce the battery lifespan and induce mechanical stress. The supercapacitor reduces the stress on the LAB by absorbing high transient currents. This, in turn, keeps the LABs’ SOC between 90% and 96% and the voltage at 12 V. As indicated by the simulated results, the hybrid battery SOC is maintained at 90–96% and the terminal voltage is approximately 12 V.

The possibilities of manufacturing batteries with Nafion 117 membranes in the Na⁺-form intercalated by mixtures of non-aqueous organic solvents used both as electrolyte, separator and binder were investigated. Electrochemical stability of various organic solvent mixtures based on N,N-dimethylacetamide, ethylene carbonate, propylene carbonate, tetrahydrofuran was characterized. It was shown that sodium battery based on Nafion-Na membrane intercalated by mixture of ethylene carbonate ‑ propylene carbonate with Na₃V_1.9Fe_0.1(PO₄)₃/C positive electrode is characterized by a discharge capacity of ca. 110 mAh g^-1 (C/10) at room temperature and shows the ability to cycle for a long time. Batteries with Nafion membrane electrolytes, containing N,N-dimethylacetamide were characterized by capacity fading during cycling, which is due to the interaction of N,N-dimethylacetamide and a negative sodium electrode.

Power system decentralization has been an emerging topic for the past decade in an effort to improve power quality and environment protection via increased integration of renewable energy sources. Towards these objectives, decentralized microgrids have been proposed and thoroughly investigated in terms of technical capabilities and economic performance. In fact, the planning and actual operation of small-scale, decentralized microgrids has started in countries such as Canada, Japan, USA, UK and other countries. It is expected that the research in this area will progress and eventually take over the existing paradigm of large-scale power generation in the future. These small-size decentralized microgrids could be connected with nearby microgrids under normal operating conditions, but under special events, such as natural or man-made disasters, they would be disconnected and run in islanded mode. Under such high impact – low probability events, the microgrid must have resiliency to successfully re-connect with other microgrids and the main grid. In this paper, an Energy Management System (EMS) for a microgrid having a resiliency function, allowing to operate under islanded mode after an accident, is proposed. The proposed tool, called Resilient Energy Management System (ResEMS), aims at procuring reserve power into the microgrid’s Battery Energy Storage System (BESS) effectively, by importing it from the nearby connected power system. The accident is assumed to be a predictable natural disaster, which means that the accident occurrence time, duration and level of damage can be estimated. The proposed ResEMS has been applied to a microgrid comprising of a BESS, a diesel generator and several photovoltaic devices. The simulation results verify its beneficial operation.

Accurate and efficient battery modeling is essential to maximize the performance of isolated energy systems and to extend battery lifetime. This paper proposes a battery model that represents the charging and discharging process of a lead-acid battery bank. This model is validated over real measures taken from a battery bank installed in a research center placed at “El Chocó”, Colombia. In order to fit the model, three optimization algorithms (Particle Swarm Optimization, Cuckoo Search, and Particle Swarm Optimization+Perturbation) are implemented and compared, being the last one a new proposal. This research shows that the model with the proposed algorithm is able to estimate and manage the real battery characteristics as SOC and charging/discharging voltage. The comparison between simulations and real measures shows that the model is able to absorb reading problems, signal delays, and scaling errors. The approach we present can be implemented in other types of batteries especially those used in stand-alone systems.

Solid-state batteries (SSBs) offer significant improvements in safety, energy density, and cycle life over conventional lithium-ion batteries, with promising applications in electric vehicles and grid storage due to their non-flammable electrolytes and high-capacity lithium metal anodes. However, challenges such as interfacial resistance, low ionic conductivity, and manufacturing scalability hinder their commercial viability. This study conducts a comprehensive scientometric analysis, examining 131 peer-reviewed SSB research articles from IEEE Xplore and Web of Science databases to identify key thematic areas and bibliometric patterns driving SSB advancements. Through a detailed analysis of thematic keywords and publication trends, this study identifies innovations in high-ionic-conductivity solid electrolytes and advanced cathode materials, which have significantly impacted performance gains and are critical to commercializing SSB technology. The findings provide actionable insights for researchers and industry stakeholders, specifically in the areas of interfacial engineering and manufacturability, where gaps in long-term stability and scalable production continue to hinder widespread adoption of SSBs. The study reveals key advances in electrolyte interface stability and ion transport mechanisms, identifying how solid-state electrolyte modifications and cathode coating methods improve charge cycling and reduce dendrite formation, particularly for high-energy-density applications. By mapping publication growth and clustering research themes, this study highlights high-impact areas such as cycling stability and ionic conductivity, providing a roadmap for targeted research efforts and strategic investments to advance SSB technology for critical applications in transportation and storage. The insights from this analysis guide researchers toward impactful areas, such as electrolyte optimization and scalable production, and provide industry leaders with strategies for accelerating SSB commercialization to extend electric vehicle range, enhance grid storage, and improve overall energy efficiency.

Rechargeable solid-state batteries (SSBs) offer enhanced safety, higher energy density, and longer cycle life compared with conventional lithium-ion batteries, making them a promising solution for electric vehicles, grid storage, and other high-demand applications. However, challenges such as interface stability, low ionic conductivity, and manufacturing scalability hinder their commercial viability. This research provides a comprehensive cross-sectional thematic and bibliometric analysis of recent SSB research, focusing on four key areas: electrolyte engineering, electrode engineering, battery architecture, and performance evaluation. By analyzing publications from major databases, this study highlights the latest innovations, including improved solid electrolytes, advanced electrode materials, and novel architectures that enhance both performance and manufacturability. The findings offer valuable insights for researchers, engineers, and industry stakeholders by identifying critical gaps in the field and highlighting future research directions. The work examines progress in interface optimization, ion transport improvements, and scalable production techniques, which are crucial for advancing SSB technology. By presenting a detailed review of key developments and challenges, this study contributes to a deeper understanding of SSB progress and its potential to revolutionize the energy storage industry. The results will guide researchers in targeting high-impact areas and help industry leaders and policymakers strategize the commercial deployment of SSBs in electric vehicles, stationary energy storage, and other applications requiring reliable and efficient energy solutions.

This paper focuses on distributed generation (DG) controller of a PV based Micro Grid. An independent DG controller (IDGC) is designed for PV applications to improve maximum power point tracking (MPPT) in Micro Grid (MG). Extreme learning machine (ELM) based MPPT method exactly estimate the reference input of converter control. They are voltage and current at MPP. Feedback controls employ linear PI schemes or nonlinear, intricate techniques. Here the converter controller, IDGC is improved by measuring directly converter outputs like duty cycle. PWM index in a single DG PV-based MG. It introduces a fast learning Extreme Learning Machine (ELM) using Moore-Penrose pseudo-inverse and an online-sequential ridge re method for robust CR estimation. The approach ensures the stability of the microgrid during PV uncertainties. Internal DG control approach (IDGC) improves the strength of the Micro Grid during, three-phase faults at load bus, partial shading, irradiance change, islanding operation and load change. The model is designed and simulated in MATLAB/SIMULINK platform and some of the results are validated in hardware in simulation (HIL) platform.

Photovoltaic modules should pass series of tests and examinations, verifying the electrical and thermal characteristics of the module, before being released to the market, examining the properties of the modules should undergo appropriate durability and efficiency tests under real outdoor conditions with exposure to climatic conditions and under laboratory conditions. The performance of photovoltaic cells depends on many factors, such as solar irradiance, module operating temperature, installation location, weather conditions and module shading. In this paper, three selected photovoltaic modules were examined using a large-scale steady-state solar simulator. The current-voltage (I-V) characteristics of the photovoltaic modules were experimentally tested and analyzed. The next step was to implement a three-layer artificial neural network model (MLP). The experimental data obtained in the previous step coupled with output data from MLP were then used in global sensitivity analysis (GSA). Experiments carried out on a large-scale stationary solar simulator showed differences between the values declared by the manufacturer and the values obtained from measurements of PV modules. The first module tested achieved the maximum power point greater than that specified by the manufacturer, while the other two showed power drops; it was 85-87% for the second module, and 95-98% for the third, respectively. The performed global sensitivity analysis (GSA) for the MLP model showed that the parameters: eff (22.9) and Voc/V (14.19) have the largest effect on the power-voltage relationship, while U (7.29) has the smallest effect. The usefulness of machine learning (ML) methods in the comparative analysis of PV modules has been proved.

Rural electrification is a crucial step for the socio-economic development of isolated communities. Decentralized power generation, typically more favorable for renewable energies, requires an accurate analysis of the different electrification options, whose convenience depends on multiple factors. The application of Geographical Information System (GIS) to energy planning allows the assessment at a local level, considering spatial resources variability and demand distribution. This work introduces IntiGIS-local, a GIS-based model implemented in ArcGIS environment, designed to calculate the Levelized Energy Cost (LEC) for different electrification options. The model allows the comparison between three power generation alternatives: solar system, diesel generator set and solar-diesel hybrid system. Configurations are adjustable through input variables, with a special focus on the confrontation between individual systems and microgrids. The objective is to provide an adequate groundwork for developing a decision-making tool to assess diverse rural electrification options in future studies. The model IntiGIS-local is tested in the case study of Guasasa community (Cuba).

Swarm electrification-driven communities face significant challenges, including implementing advanced distributed control in areas with limited ICT access and establishing trust among villagers hesitant to grant access to their assets. This paper proposes a distributed DC microgrid architecture for P2P energy exchange in these communities, ensuring stability and effective exchange operation. By implementing a Blockchain marketplace specifically designed to suit the rural context, the proposed architecture ensures tracing of exchange transactions to fairly settle participants. Validation experiments demonstrate its efficacy in achieving peak shaving. It provides 11% of the requester's total demand from the community even while maintaining the constraint of reducing discharge-charge cycles to one per day, thereby preserving battery life. Additionally, the solution reduces prosumer production losses by 16% of the total PV production.

Soiling accumulated on a photovoltaic (PV) module can significantly reduce the transmittance of the cover glass, resulting in power losses and consequent economic losses. Natural atmospheric parameters influence the accumulation of soiling at the various geographic locations. In this paper, the approaches and outcomes of the research studies on either indoor (simulator-based) or outdoor (field-based) PV soiling have been thoroughly reviewed. Different parameters depicted for the power loss of PV modules are analyzed individually and presented. Moreover, this study delves into a detailed examination of the key factors influencing dust depositions on PV modules in various geographical regions, with a particular focus on their relationship with climatic conditions. This way, probable future research directions to quantify soiling losses are identified. In addition, different loss prevention and mitigation techniques are also reviewed. This makes it possible to highlight effective strategies and pinpoint potential future research lines in these areas.

This research paper presents a comprehensive study on the optimal planning and design of hybrid renewable energy systems for microgrid (MG) applications at Oakland University. The HOMER Pro platform analyzes the technical economic and environmental aspects of integrating renewable energy technologies. The research also focuses on the importance of addressing unmet load in the MG system design to ensure the university's electricity demand is always met. By optimizing the integration of various renewable energy technologies, such as solar photovoltaic (PV), energy storage system (ESS), combined heat and power (CHP), and wind turbine energy (WT), the study aims to fulfill the energy requirements while reducing reliance on traditional grid sources and achieving significant reductions in greenhouse gas emissions. The proposed MG configurations are designed to be scalable and flexible, accommodating future expansions, load demands changes, and technological advancements without costly modifications or disruptions. By conducting a comprehensive analysis of technical, economic, environmental factors, and addressing unmet load, this research contributes to the advancement of renewable energy integration within MG systems. It offers a complete guide for Oakland University and other institutions to effectively plan, design and implement hybrid renewable energy solutions, fostering a greener and more resilient campus environment. The findings demonstrate the potential for cost-effective and sustainable energy solutions, providing valuable guidance for Oakland University in its search of energy resilience and environmental surveillance which has a total peak load of 9.958MW. The HOMER simulation results indicate that utilizing all renewable resources, the estimated net present cost (NPC) is a minimum of 30M$, with a levelized energy cost (LCOE) of 0.00274$/kWh. In addition, the minimum desired load will be unmeted on some days of September.