The thermoelectric generator (TEG) stands out in many energy harvesters due to its simple structure, small size, etc. However, previous studies rarely probe into the influence of TEG internal resistances on extracting maximum power from TEG, and tracking efficiency is limited. By analyzing the relationship between the tracking efficiency and the TEG internal resistances, a time exponential rate perturbation and observation (P&O) technology is proposed to achieve maximum power point tracking (MPPT) for a wide resistance range of TEG. Using the time exponential rate P&O, the MPPT circuit observes the power change by comparing PMOS on-time and perturbs the power by adjusting NMOS on-time exponentially. The MPPT circuit is implemented in a 110nm CMOS process. The tracking efficiency keeps a high level from 98.9 to 99.5%. The applicable range of the TEG resistance is from 1 to 12Ω, which is enhanced at least 2.2 times.

This policy paper explores various strategies that would facilitate transitioning the traditional Jordanian electrical grid to a secure smart grid. It includes comprehensive recommendations from academia and industry for the regulatory and governmental sector in Jordan to achieve specific roadmap objectives. As Jordan is heavily dependent on fossil fuels, This policy paper also provides recommendations for incorporating more renewables into its energy mix, thereby facilitating a sustainable future. The proposed policies will emphasise the creation of an enabling environment where innovation, research, and development initiatives flourish, thereby promoting private sector engagement.

The scope of this work was part of our previous research on Pulsed Power Plasma Stimulation Technique. Electromagnetic fields generated during a pulsed power plasma discharge were simulated using a finite element method in the COMSOL RF module. The field distributions were calculated during and after the pulse. The current paper takes advantage of prior work measuring and modeling the current distribution in the plasma arc. Agreement with laboratory experimental measurements provides support for extension of the model to reservoir scale. The validated model was used to quantify the signal attenuation level in different medium environment.

This article is a big picture of how electrical noise or conducted Electromagnetic Interference (EMI) is generated and mitigated in power converters. It gives an overview of what EMI in power converters is – from generation through to conduction and mitigation. It is meant to cover the complete subject as a summary so that the reader will have an outline of how to control conducted EMI by design (where possible) and how to mitigate by filtering. A clear distinction is made between Differential Mode (DM) and Common Mode (CM) EMI generation and mitigation. By using a boost converter as an example the trade-offs for DM noise control are discussed. It is shown how CM EMI is generated in a boost converter using the concept of the “Imbalance Difference Model” (IDM). Practical measurements for an in-line power filter is given showing the effect of the filter on the total EMI of a boost converter. Measurements for the CM current produced due to the imbalance difference for different values of the boost conductor are also shown. The main contribution of this study is linking CM noise generation to DM EMI. It is shown that CM noise is a direct consequence of DM noise (although circuit imbalance and coupling to a common ground also play a role). This paper will be useful to designers seeking the “bigger picture” of how EMI is generated in power converters and what can be done to mitigate the noise.

Let be a power function $f_{r,M}(s)$ defined for every $s$ within the finite set $M$ as follows $$f_{r,M}(s)= \begin{cases} s^r, \ &s\in M,\\ 0, \ &\mathrm{otherwise}. \end{cases} $$ Let a discrete convolution of $f_{r,M}(s)$ be denoted as follows $\mathrm{Conv}_{r,M}[n]=(f_{r,M}*f_{r,M})[n]$. Let a real coefficients $A_{m,j}$ be given by the following recurrence $$ A_{m,j} = \begin{cases} 0, & \mathrm{if } \ j<0 \ \mathrm{or } \ j>m, \\ (2j+1)\binom{2j}{j} \sum_{d=2j+1}^{m} A_{m,d} \binom{d}{2j+1} \frac{(-1)^{d-1}}{d-j} B_{2d-2j}, & \mathrm{if } \ 0 \leq j < m, \\ (2j+1)\binom{2j}{j}, & \mathrm{if } \ j=m. \end{cases} $$ In this paper we show that for every $n>0$ the following odd-power identities involving coefficients $A_{m,j}$ and convolution transform $\mathrm{Conv}_{r,M}[n]$ hold $$ \begin{split} n^{2m+1}+1&=\sum_{r=0}^{m}A_{m,r}\mathrm{Conv}_{r,\mathbb{N}}[n],\\ n^{2m+1}-1&=\sum_{r=0}^{m}A_{m,r}\mathrm{Conv}_{r,\mathbb{Z}_{>0}}[n],\\ n^{2m+1}&=\sum_{r=0}^{m}A_{m,r}\sum_{k=1}^{n} k^r(n-k)^r\\ &=\sum_{r=0}^{m}A_{m,r}\sum_{k=0}^{n-1} k^r(n-k)^r. \end{split} $$

FACTS devices provide significance to enhance the functioning of both static and dynamic power systems. The type, size, and location of FACTS devices determine how well they achieve the goals of enhancing voltage stability, loadability, and loss minimization simultaneously. The aim of the function in this study includes voltage stability, line loadings, and loss minimization, which are expected to obtain the most benefits from their installation and other weights allocated to them. It has been determined how installing TCSC, and SVC will improve loadability under situations of continuously increasing load. In this study, a novel optimization technique known as differential evolution invasive weed optimization (DEIWO) is utilized to locate the optimal location for FACTS devices within the IEEE 14 bus system by considering valve point effects. DEIWO was a recently developed, dominant, and simple metaheuristic algorithm for genuine parameter optimization. DEIWO was inspired by the natural process of weed colonization and dissemination, and it is highly effective at addressing broad multi-dimensional, linear and nonlinear optimization problems. The proposed method was implemented in the IEEE 14 bus testing system. Different methods from the research papers have been used to compare and analyze the results. The results demonstrate the DEIWO algorithm's capability and show how it may be used in practice to locate FACTS devices in deregulated electricity networks in the most advantageous place. A comparison of the proposed process to existing algorithms found in the literature and implemented using traditional techniques reveals that it performs better in terms of precision and convergence

Microgrids can be islanded to improve the reliability of the electrical energy supply during contingencies such as faults. It is still unclear what stability phenomena can occur in microgrids without inertia during and immediately after the fault-initiated islanding transient, and how the stability should be evaluated. To allow robust planning and operation, a stability analysis methodology should be able to take into account the inherent uncertainty of load and renewable energy sources. Therefore, this paper proposes a probabilistic stability analysis methodology for fault-initiated islanding of microgrids based on a thorough analysis of the root causes of instability during islanding transients. To perform stability analysis within reasonable time and allow control actions during operation, dynamical microgrid models in the dq reference frame are described and validated by comparing time-domain simulations results to previously validated component-based models. The stability analysis methodology is demonstrated in a case study of a generic microgrid. The instability phenomena and the dq microgrid models are successfully validated, and the results indicate that the stability analysis methodology can assist the microgrid operator to improve fault-initiated islanding capability in order to improve reliability of supply.

One of the most crucial and economically beneficial tasks for energy customer is peak load curtailment. On account of the fast response of renewable energy resources (RERs) such as photovoltaic (PV) units and battery energy storage system (BESS), this task is closer to be efficiently implemented. Depends on the customer peak load demand and energy characteristics, the feasibility of this strategy may warry. When adaptive neuro-fuzzy inference system (ANFIS) is exploited for forecasting, it can provide many benefits to address the above-mentioned issues and facilitate its easy implementation, with short calculating time and re-trainability. This paper introduces a data driven forecasting method based on fuzzy logic for optimized peak load reduction. First, the amount of energy generated by PV is forecasted using ANFIS which conducts output trend, and then, the BESS capacity is calculated according to the forecasted results. The trend of the load power is then decomposed in Cartesian plane into two parts, left and right from load peak, searching for BESS capacity equal. Network switching sequence over consumption is provided by a fuzzy logic controller (FLC) with respect to BESS capacity and PV energy output. Finally, to prove the effectiveness of the proposed ANFIS-based peak shaving method, offline digital time-domain simulations have been performed on a real-life practical test micro grid system in MATLAB/Simulink environment and the results have been experimentally verified by testing on a practical micro grid system with real-life data obtained from smart meter and also, compared with several previously-reported methods.

Penetration of grid connected inverters (GCI) has arisen in power systems due to increasing integration of renewable sources. However, restrictive grid codes require that renewable sources connected to the grid with power electronic systems must be properly connected and appropriate currents must be injected to support stability of the grid under grid faults. Simultaneous injection of symmetrical positive and negative sequence currents is mandatory to support stabilization of grid at the instant of grid faults. Conventional synchronously rotating frame dq current controllers are insufficient under grid faults due to low bandwidth of PI controllers. This paper proposes a new grid current control strategy for grid connected voltage source inverters under unbalanced grid voltage conditions. A proportional current controller with a first order low pass filter disturbance observer (DOb) is proposed which establishes positive sequence power requirements and independently control negative sequence current components under unbalanced voltage conditions. The method does not need any parameter, since it estimates nonlinear terms with low pass filter DOb. Simulations are implemented in Matlab/Simulink platform demonstrating the effectiveness of proposed method.

Reference evapotranspiration (ET0) is the first step in calculating crop irrigation demand, and numerous methods have been proposed to estimate this parameter. FAO-56 Penman-Monteith (PM) is the only standard method for defining and calculating ET0. However, it requires radiation, air temperature, atmospheric humidity, and wind speed data, limiting its application in regions where these data are unavailable; therefore, new alternatives are required. This study compared the accuracy of ET0 calculated with the Blaney-Criddle (BC) and Hargreaves-Samani (HS) methods versus PM using information from an automated weather station (AWS) and the NASA-POWER platform (NP) for different periods of time. The information collected corresponding at Module XII of the Lagunera Region Irrigation District 017, a semi-arid region in the North of Mexico. The HS method underestimated by 5.5 % the reference evapotranspiration (ET0) compared to the PM method during the period from March to August, and yielded the best fit in the different evaluation periods: daily, average, and 5-day cumulative; the latter showed the best values of inferential parameters. The information about maximum and minimum temperatures from the NP platform was suitable for estimating ET0 using the HS equation. This data source is a timely alternative, particularly in semi-arid regions where no data from weather stations are available.

The goal of this paper is to present a low-cost, low-power prototype of a pulsed Ultra Wide Band UWB) oscillator and an UWB elliptical dipole antenna integrated on the same Radio Frequency (RF) Printed Circuit Board (PCB) and its digital control board for Real Time Locating System (RTLS) applications. The design is compatible with IEEE 802.15.4 high rate pulse repetition UWB standard being able to work between 6 GHz and 8.5 GHz with 500 MHz bandwidth and with a pulse duration of 2 ns. The UWB system has been designed using the CST Microwave Studio transient Electro-Magnetic (EM) circuit co-simulation method. This method integrates the functional circuit simulation together with the full wave (EM) simulation of the PCB’s 3D model allowing fast parameter tuning. The PCB has been manufactured and the entire system has been assembled and measured. Simulated and measured results are in excellent agreement with respect to the radiation performances as well as the power consumptions.

An ultra-low power (ULP), power gated static random access memory (SRAM) is presented for Internet of Things (IoT) applications, which operates in sub-threshold voltage ranges from 300mV to 500mV. The proposed SRAM has tendency to operate in low supply voltages with high static and dynamic noise margins. The IoT application involves battery enabled low leakage memory architecture in subthreshold regime which has low power consumption. Therefore, to improve power consumption along with better cell stability, a power gated 10T SRAM is presented. The proposed cell uses a power gated p-MOS transistor to reduce the leakage power or static power in standby mode. Moreover, due to the schmitt triggering and read decoupling of 10T SRAM the static and dynamic behavior in read, write and standby mode has shown enhanced tolerance at different process, voltage and temperature (PVT) conditions. The proposed SRAM shows better results in terms of leakage power, read static noise margin (RSNM), write static noise margin (WSNM), write-ability or write trip point (WTP), read-write energy and dynamic read margin (DRM). Further, these parameters are observed at 8-Kilo bit (Kb) and compared with already existing SRAM architectures. It is observed that the leakage power is reduced by 1/81×, 1/75× of the conventional 6T (C6T) SRAM and read decoupled 8T (RD8T) SRAM, respectively at 300mV VDD. On the contrary, RSNM, WSNM, WTP and DRM values are improved by 3×, 2×, 11.11% and 31.8% as compared to C6T SRAM, respectively. Similarly, proposed 10T has 1.48×, 25% and 9.75% better RSNM, WSNM and WTP values as compared to RD8T SRAM, respectively at 300mV VDD.

To supply stable and high-quality power according to the advancement of industrial growth, electric power companies have performed maintenance of power facilities using various meth-ods. In the case of domestic power distribution facilities, there are limitations in performing di-agnostic management on all facilities owing to the large number of facilities; therefore, old fa-cilities are managed by the health index assessment method. The health index assessment com-prises only facility operation data and external environmental data and is managed only for four types of distribution facilities, including overhead/underground transformers and switchgear. In the case of extra high–voltage overhead wires, there is no standard for old replacement, despite the large number of wires, such as transformers and switchgear, and the large ripple effect of power failure in the event of a power outage. Therefore, in this paper, a health index assessment methodology for extra-high voltage overhead cables was developed. In this paper, we devel-oped an economic health index assessment methodology that additionally considers risk cost, which is different from the existing health index assessment method that uses only operational data and external environmental data to determine facility performance evaluation and aging replacement criteria. Using the health index assessment methodology developed in this paper, it is possible to expect a reduction in facility operating costs and investment costs from the per-spective of electric power companies through the replacement of old extra-high voltage over-head cables. In addition, from the perspective of consumers, it is expected to increase power re-liability and reduce the ripple effect of failure by preferentially replacing equipment with a high probability of failure.

The present review article concludes with three different types of materials recently used to enhance the efficiency of supercapacitors. The first type involves carbon-based materials for storage and supercapacitor applications. The carbon materials could be obtained naturally and synthesized manually based on the needs. The second type discusses the recent advances in metal oxide materials for high-performance supercapacitors. The metal oxide materials involve in different types of attachment through the bi-tri metallic bonding, which enhances the specific capacitance. The third type involves recently advanced materials for high energy and power density application. The power and energy density of the materials is enhanced by the surface modification of the materials. In recent days, the MXene and Nano-composite materials seems to be an appropriate material to increase the power and energy density of the device.

The increasing variability in power plant load, in response to a wildly uncertain electricity market and the need to to mitigate CO₂ emissions, lead power plant operators to explore advanced options for efficiency optimization. Model-based, system-scale dynamic simulation and optimization are useful tools in this effort, and the subject of the work presented here. In prior work, a dynamic model validated against steady-state data from a 605 MW subcritical power plant was presented. This power plant model is used as a test-bed for dynamic simulations, in which the coal load is regulated to satisfy a varying power demand. Plant-level control regulates plant load to match an anticipated trajectory of the power demand. The efficiency of the power plant operating at varying load is optimized through a supervisory control architecture that performs set point optimization on the regulatory controllers. Dynamic optimization problems are formulated to search for optimal time-varying input trajectories that satisfy operability and safety constraints during the transition between plant states. An improvement in time-averaged efficiency of up to 1.8% points is shown feasible with corresponding savings in coal consumption of 184.8 tons/day and carbon footprint decrease of 0.035 kg/kWh.

Frontotemporal dementia (FTD) is the second most common form of presenile dementia; however, its diagnosis has been poorly investigated. Previous attempts to diagnose FTD using quantitative electroencephalography (qEEG) have yielded inconsistent results in both spectral and functional connectivity analyses. This study aimed to introduce an accurate qEEG marker that could be used to diagnose FTD and other neurological abnormalities. We used open-access electroencephalography data from OpenNeuro to investigate the power ratio between the frontal and temporal lobes in the resting state of 23 patients with FTD and 29 healthy controls. Spectral data were extracted using a Fast Fourier Transform in the delta (1–4 Hz), theta (4–8 Hz), alpha (8–13 Hz), beta (13–32 Hz), and gamma (32–45 Hz) bands. We found that the spectral power ratio between the frontal and temporal lobes is a promising qEEG marker of FTD. Frontal/temporal (F/T) theta/alpha, alpha/theta, al-pha/gamma, and gamma/alpha showed a consistently high discrimination score for the diagnosis of FTD for different parameters and referencing methods. The study findings can serve as reference for future research focused on diagnosing FTD and other neurological anomalies.

The maritime sector, grapples with environmental challenges, but the adoption of "cold ironing" emerges as a promising solution, signifying a shift toward sustainability by providing energy to ships at port, reducing reliance on fossil fuels, and significantly lowering emissions, contributing to global climate change efforts. This transition towards renewable energy is especially crucial for islands like Lesvos, addressing challenges of high energy costs and environmental degradation resulting from reliance on imported fossil fuels, highlighting the potential for positive economic and environmental impacts. The existing literature highlights a research gap in the development of Renewable Energy Sources (RES) to support cold ironing operations, specifically due to the absence of specific data for the power demand needed in such operations and the lack of monitoring data for accurate calculations. This study's primary objective is to utilize real monitoring data from the port of Lesvos to evaluate the power demand for a potential cold ironing application. Additionally, the study aims to analyze the implementation of a wind power park to meet the energy needs of an electric port and evaluate the potential reduction in CO2 emissions. The database of Marine Traffic S.A. was utilized, while the determination of the energy used in-port per ship depended on factors such as the number of arrivals, the duration of hoteling, and the type of engine used by the ships. In addition, the software RETSCREEN was used for the energy analysis of a simulated 20 MW wind park that can support the in-port operations. The combined monthly energy demand for both main and auxiliary engines of shipping vessels at Mytilini port was assessed to be 6118 MWh and averaging a power demand equaled to 8.2 MW. The simulation analysis indicates that the annual electricity delivered to the port can be72080 MWh, with a significant portion remaining unused and exported to the grid, amounting to 14956 MWh annually. Due to demand fluctuations, in-port activities require an additional 924 MWh from the main electrical grid, which highlights the importance of additional measures like energy storage and demand-response practices for the gradual transition to 100% Renewable Energy Sources (RES) operations.

This paper proposes a position recognition method for the receiver coil by the secondary coil current. Based on the practical value of the current of the receiver coil, the position recognition of the receiver coil in the WPT system is realized. This paper proposes a 3×3 array multi-transmitter coil grouping and control logic. The mathematical model of mutual inductance between the receiver and transmitter coil at different positions on the X-Y plane is established. A method for identifying the position of the receiver coil according to the current of the receiver coil is proposed. Compared with the traditional position recognition method of the receiver coil, this method does not need to add a detection coil and position sensor and can realize the position recognition of the receiver coil on the 2D plane.

Photovoltaic(PV) power generation is highly nonlinear and stochastic. Accurate prediction of PV power generation plays a crucial role in grid connection as well as the operation and scheduling of power plants. To predict the PV power combination model, this paper suggests a method based on Empirical Mode Decomposition (EMD), Ensemble Empirical Mode Decomposition (EEMD), Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN), Nonlinear Auto-Regressive Neural Networks with Exogenous Input (NARXNN), Long Short Term Memory (LSTM) Neural Network, and Light Gradient Boosting Machine (LightGBM) algorithms. To attempt to reduce the non-smoothness of PV power, the weather variable features with the greatest effect on PV power are first identified by correlation analysis. Following this, the PV power modal decomposition is split and reorganized into a new feature matrix. Finally， a NARX is used to obtain preliminary PV power components and residual vector features， and the PV power is predicted by combining three models of LightGBM， LSTM, and NARX and then the final prediction results are obtained by combining the PV power prediction results using error inverse method weighted optimization. The prediction results demonstrate that the model put forth in this paper outperforms those of other models and validate the model's validity by utilizing real measurement data from Andre Agassi College in the United States.

This study investigates the power production and blade fatigue of a three-turbine array subjected to active yaw control (AYC) in full-wake and partial-wake configurations. A framework of two-way coupled large-eddy simulation (LES) and aeroelastic blade simulation is applied to simulate the atmospheric boundary-layer (ABL) flow through the turbine array and the structural responses of the turbine blades. Mean power outputs and blade fatigue loads are extracted from the simulation results. By exploring the feasible AYC decision space, we find that (a) in the full-wake configuration, the local power-optimal AYC strategy with positive yaw angles endures less flapwise blade fatigue and more edgewise blade fatigue than the global power-optimal strategy; (b) in the partial-wake configuration, applying positive AYC in certain inflow wind directions achieves higher optimal power gains than that in the full-wake scenario and reduces the blade fatigue from the non-yawed benchmark. Through a theoretical analysis based on the blade element momentum theory, we reveal that the aforementioned differences in flapwise blade fatigue between the positively and negatively yawed turbine are due to the differences in the azimuthal distributions of the local relative velocity on blade sections, resulting from the combined effects of vertical wind shear and blade rotation. Furthermore, the difference in the blade force between the positively and negatively yawed front-row turbine induces different wake velocity and turbulence distributions, causing different fatigue loads on the downwind turbine exposed to the wake.

In this paper, we investigate an analytical solution of a class of nonlinear fractional integro-differential equation base on a generalized fractional power series expansion. The fractional derivatives are described in the conformable's type. The new approach is a modified form of the well-known Taylor series expansion. The illustrative examples are presented to demonstrate the accuracy and effectiveness of the proposed method

This study conducts a comprehensive review of the integration of Hybrid Electric Turbochargers in mass-produced road vehicles. The primary objective is to inform the readers about the potential advantages and innovative applications of HETs. Employing a SWOT analysis, the research compares the performance of HETs on thermal engines versus traditional turbochargers and HETs on thermal engines versus HETs on hybrid engines based on a synthesis of multiple research findings. The study elucidates the fundamental mechanics of turbochargers, emphasizing their inherent benefits. Additionally, it introduces a novel approach with the integration of the hy-brid-electric turbocharger, demonstrating its capacity, supported by practical examples. The in-corporation of turbochargers with energy recovery mechanisms, including HETs, is shown to significantly contribute to emissions reduction. Moreover, the electric drive facilitates the utili-zation of hybrid turbines, particularly on low-displacement engines, resulting in enhanced effi-ciency, torque, and liter power. In conclusion, the research underscores the potential of HETs to substantially mitigate the environmental impact of the transportation sector by reducing emis-sions and conserving energy. Their ability to optimize the fuel efficiency and power output of internal combustion engines, coupled with the feasibility of downsized engines, positions HETs as an attractive option for both manufacturers and consumers. However, it is acknowledged that the implementation of HETs is in its early stages, necessitating further research to comprehensively understand their environmental impact. Despite this, the promising positive impact on the en-vironment designates HETs as a technology deserving close attention in the forthcoming years.

Energy transitions are reshaping the global energy system. Such shift has taken the power system to become a critical infrastructure for achieving economic development of every nation in the planet, therefore, guaranteeing its security is crucial, not only for energy purposes but as a part of a national security strategy. This paper presents a multi-dimensional index developed to assess energy security of electrical systems in the long term. This tool, named Power System Security Index (PSIx), and which has been previously used for the evaluation of a country in two different time frames, is applied to evaluate the member countries of the Latin American Energy Organization, located within the Latin America and the Caribbean region, in order to measure their performance on energy security. Mixed results were obtained from the analysis, with clear top performers in the region such as Argentina, while there are others with broad areas of opportunity, as it is the case of Haiti.

Given the imperative of security, sustainability of supply, strategic considerations, and energy independence, there is a widely acknowledged need to persist in utilizing coal as the primary fuel for electricity generation in power plants. However, in order to combat the rising levels of CO2 in the atmosphere, it is crucial to advance the development of carbon capture and storage (CCS) technologies that enable fossil fuel power plants to achieve zero emissions. These technologies play a pivotal role in capturing and effectively storing CO2, thus ensuring that coal-based power generation can continue while significantly reducing its environmental impact. By implementing CCS solutions, fossil fuel power plants can transition towards a more sustainable and environmentally friendly energy future.The utilization of chemical solvents for CO2 absorption, coupled with long-term storage, presents an intriguing and commercially viable technology for CO2 capture. However, the significant energy demands of the solvent regeneration process necessitate optimization, particularly in large-scale power plants. While the current cost of CO2 capture stands at approximately #55,000.00(Naira) per ton of CO2, the objective is to reduce this cost to below #25,000.00(Naira) per ton of CO2. This reduction in cost is essential to ensure the economic feasibility and widespread adoption of CO2 capture technologies in power generation.This research paper explores various approaches to address the energy demands associated with amine scrubbing integration in a commercial power plant. It provides a comprehensive analysis, both technically and economically, of the performance of these different approaches. While some of the proposed schemes may result in minor efficiency reductions, the key objective is to calculate the specific cost per ton of CO2 captured. The primary focus is on identifying the most suitable configuration to implement large-scale, cost-effective schemes that can serve as a foundation for CO2 capture demonstration projects. By determining the optimal configuration, this research aims to pave the way for the successful implementation of efficient and economically viable CO2 capture technologies in the power generation sector.

Currently, one of the main focuses of attention in academia is microgrids (MGs) and their ability to maintain stable, resilient, reliable and high–power quality operations. A crucial component in MGs is power converters (PC), which facilitate the decentralization of power generation. This decentralization, however, poses challenges in terms of power quality. This paper presents a microgrid model based on the IEEE 14–bus distribution system and aims to investigate the power quality when the MG operates while connected to the conventional power grid. The MG model has been developed using MATLAB–Simulink®, a specialized tool for electrical engineering simulations. The results obtained are subjected to rigorous analysis and compared with the compatibility levels established by the IEEE–519 standard. This approach allows an accurate assessment of the MGs’ ability to maintain power quality at acceptable levels while interconnected to the conventional power grid. Finally, this study provides a valuable contribution to the MGs’ field of microgrids by providing a detailed and quantitative assessment of power quality, which will aid in the design and optimization of MGs’ for effective implementation in real electric power systems.

The design of highly efficient sensitizers is one of the most significant areas in dye-sensitized solar cell (DSSC) research. We have studied a series of benzothiadiazole-based D-π-π-A organic dyes, putting emphasis on the influence of the donor moiety on the DSSC’s efficiency. Using linear response time-dependent density functional theory (TDDFT) with the CAM-B3LYP functional different donor groups were characterized in terms of electronic absorption spectra and key photovoltaic parameters. As a reference a dye has been considered which has a benzothiadiazole fragment linked via thiophene rings to a diphenylamine donor and a cyanoacrylic acid acceptor. The different systems are first studied in terms of individual performance parameters, which are eventually aggregated into the power conversion efficiency. Here only the amino-substituted species shows a modest increase, whereas the dimethylamino case even shows a decrease.

The growing need to use renewable sources and the current difficulty in spreading the electricity grid in a widespread manner raise the question of how to respond to the need for more electricity immediately. The idea behind this study is to power a horizontal axis wind turbine with the air flow generated for cooling a stationary internal combustion engine. The power extracted from this solution is significantly lower than that of the internal combustion engine (about 0.3%) and could be advantageous only in limited contexts. Installation costs are limited because many elements deriving from wind variability can be removed or simplified.

This study analyzes the correlation between the lifetime and the rest energy of the unstable particle states with a lifetime greater than the zeptosecond (10⁻²¹ s), using data available from the Particle Data Group. This set of states seems to be divided into three groups, in each of which the two quantities can be correlated through a remarkably accurate power law. Although this fact does not represent anything new compared to the predictions of the Standard Model, it nevertheless reveals an unexpected order structure in the set of particle decays, emerging from such predictions.

Purposely slow velocity resistance exercise (i.e., 10 s concentric and eccentric phases) is a popular training method, but limits the loads that can be lifted (e.g., <50% 1 RM). This study compared the biomechanical properties of purposely slow velocity (SLOW) and traditional resistance exercise (TRAD) that uses maximal lifting velocities. Healthy resistance-trained men (n=5) performed two testing sessions (barbell squat and bench press) in random-order; a SLOW session (1 set x 10 repetitions at 28% 1 RM, 10 s concentric & eccentric), and a TRAD session (3 x 10 at 70% 1 RM, controlled eccentric and maximal concentric). A force plate and linear position transducer were used to collect kinetic and kinematic data for every repetition of both protocols (α = 0.05). For both exercises, both concentric and eccentric mean force (N) and power (W) for each repetition was greater for TRAD. When the entire training session (squat + bench press) was examined, SLOW exhibited greater time under tension, while TRAD produced greater work (J) and impulse (N·s). Contrary to suggestions in both the lay and scientific literature, purposely slow resistance exercise produced less force, power, and work than traditional velocity resistance exercise.

For the particular selected type of fractals, i.e., the Kronecker product based fractals, the introductory common classification is proposed. It essentially relies on the size and content of the initial fractal matrix. In turn, it gives one of the possible explanation of the phenomenal ability to produce a few of the most popular fractals using many different algorithms, languages and tools. Also, it paves the way to discover on the regular basis thousands of the new fractals, and this gives researchers a wider range of fractal models to choose from.

Multi-board electronic cases with high density and high power modules are widely used in industrial power supply management. With the improvement of case performance and miniaturization requirements, heat dissipation becomes one of the important factors to be considered in the design process. First,The existing small electronic thermal design methods focus on heat dissipation structure or heat source layout optimization,and ignores on-load test for modeling analysis. Second,The selected power module has on-load power consumption, resulting in relatively low calorific value and the effectiveness of thermal design cannot be verified. Third, The thermal lacks Intelligent monitoring and feedback control mechanism. In order to solve these problems, this paper designs a kind of heat dissipation case with intelligent temperature control based on high-power and high-density power supply array. Based on the extremely miniaturization design principle, we adopt the composite heat dissipation mode based on conduction and supplemented by forced air cooling . The case is made of magnesium and aluminum alloy with a perforated design. Finally, we compare and analyze with the existing cooling design. The results show that the case is smaller in volume, and the cooling performance parameters are slightly better than the existing case. Under the condition of high-density and high-power design, The output power of the whole system is not less than 10kw and the lowest packing-level density is not less than 47w/cm2 with high reliability, portability and practicability. It also provides technical support and prototype support for the standardized design of similar power arrays.

In response to the problem of increasing climate change and energy security, investment in renewable energy sources has increased significantly both in Europe and globally. Wind and solar power plants are expected to be the largest contributors to global decarbonization, ranking first and second in projected capacity by 2050. Since all power plants have some impact on the environment, this also applies to photovoltaic power plants. Because of the large capacities projected for PV installed capacity, their environmental impacts should be evaluated. The environmental impacts of PV power plants change over time. Improving the manufacturing technology of PV system components, increasing the efficiency of solar cells, and using materials that are less harmful to the environment will reduce these impacts. Manufacturing PV system components is a highly energy-intensive process that involves greenhouse gas emissions. As new renewable energy capacity is built, the amount of "green" electricity on the grid increases, reducing CO2 emissions per kWh consumed. The objective of this paper is to analyze the current status of the environmental impact of PV power plants under these changing conditions in terms of CO2 emissions, land use, pollutant and noise emissions, and water consumption. The capacity installed to date will reach the end of its lifetime by 2050, which means that the amount of waste associated with it will increase over time. This can have a significant impact on the environment, which is why part of the work is dedicated to this problem. In addition to the available information from the literature, in the part related to land use, the authors also made their own estimates based on data on newly installed PV power plants and PV modules available on the market. The results of the analysis show that there is enough land both in Europe and worldwide to install the planned capacities of rooftop and ground-mounted PV power plants. CO2 emissions are at the same level as for concentrated solar power, with a decreasing trend. Pollutant emissions, noise and water consumption are not a major problem compared to other types of power plants. Overall, it can be concluded that the expansion of PV capacity has a very positive impact on the environment.

Over the last ten years, the integrated pond aquaculture (IPA) has been developing rapidly as a new aquaculture mode, and mechanical power oxygenator is a common oxygenation device in this aquaculture mode. However, with the gradual expansion of the application range of this aquaculture mode, the problems of low efficiency, poor oxygenation uniformity, and low applicability of mechanical power oxygenators, which can produce water reflux and suction pollution accumulation, have gradually emerged. Therefore, we designed a new type of push-water aerator device (NPWAD) applicable to the integrated recirculating water aquaculture mode of ponds. Mainly, the specific parameters of the key components were clarified through the selection calculation and structural design, and the experiments were carried out in the self-constructed pond integrated aquaculture system at the experimental base. The experiments were carried out on the water in the tank for grass carp culture, and the oxygenation and water pushing effects of the type of push-water aerator device under 15 groups of different operating parameters were carried out by using multiple types of high-precision water quality monitoring sensors, with the rotational speed of the device, the operating time (0-30 min) and the height of the water (0.5-1.5 m) as the independent variables, and the oxygenation amount R, the oxygenation power efficiency E_s and the surface layer of the water as the evaluation indexes, average flow velocity V_f were used as its evaluation indexes of oxygenation and water pushing. The results show that the optimal parameters of the NPWAD are impeller water lifting component speed n_1=1000r/min, small-hole aeration component speed n_2=2280r/min. At this time, the average oxygen increase of this device is R=1.96mg/L, the average oxygenation power efficiency is E_s=3.8 kg·(h·kW)-1, the DO uniformity of the water M_1=95.3%, and the average flow velocity V_f=190.8mm/s, which can effectively promote the water directional flow and achieve the water circulation and layer exchange, and it is in line with the preferred swimming speed of grass carp at various growth stages. The new type of push-water aerator device is able to enhance the DO concentration of the water faster, but also to achieve the purpose of promoting the directional flow of the water and renewing the water in the tank, as well as in a short period of time to improve the uniformity of the DO of the water faster, for the improvement of the pond aquaculture production efficiency has practical significance.

Power and energy efficiency are among the most crucial requirements in high-performance and other computing platforms. This work examines through extensive experimentation methods and procedures suitable for assessing the power and energy efficiency of fundamental hardware building blocks inside a typical high-performance CPU, focusing on the dynamic branch predictor (DBP). The investigation relies on the Running Average Power Limit (RAPL) interface from Intel, a software tool for credibly reporting the power and energy based on instrumentation inside the CPU. We use well-known microbenchmarks under various run conditions to explore potential pitfalls and to develop precautions to raise the precision of the measurements obtained from RAPL for more reliable power estimation. The authors discuss the factors that affect measurements and share the difficulties encountered and the lessons learned.

Natural gas combined cycle power plants (CCPPs) are widely used to meet peak loads in electric energy production. Continuous monitoring of the output electrical power of CCPPs is a requirement for power performance. In this study, the role of ambient temperature change having the greatest effect on electric production is investigated for a natural gas CCPP. The plant has generated electricity for fourteen years and setup at 240 MW in Aliağa, İzmir, Turkey. Depending on the seasonal temperature changes, the study data were obtained from each gas turbine (GT), steam turbine (ST) and combined cycle blocks (CCBs) in the ambient temperature range of 8-23°C. It has been found that decreases of the electric energy in the GTs because of the temperature increase and indirectly diminishes of the electricity production in the STs. As a result, the efficiency of each GT, ST and CCB reduced, although the quantity of fuel consumed by the controllers in the plant was decreased. As a result of this data, it has been recommended and applied that additional precautions have been taken for the power plant to bring the air entering the combustion chamber to ideal conditions and necessary air cooling systems have been installed.

Ultralight power generation equipment has high requirements for the power density, continuous operation, and transient stability of the whole machine, and there is a direct conflict between high power density design and substantial stability control in the power unit design. In order to meet the power density requirements of ultra-light power stations, three main problems need to be solved, namely engine speed oscillation and flameout in the process of load power mutation, matching of the generator and engine torque, and stabilizing the voltage waveform of the AC output end. In this paper, we proposed an exquisite control strategy for ultralight power generation systems in engines, generators, and inverters. The effectiveness and practicability of the proposed strategy are verified by both simulation and experiment. The results show that the proposed control strategy can effectively solve the instability problem of the ultralights generator set and improve the stability of the system, where the response recovery can be achieved within 0.9 seconds under the condition of total load increase or decrease, and the mismatching degree of the generator following the engine is reduced by 90%. The strategy could also guarantee long-term stable operation with high-quality electrical energy output.

Comparisons of power flows and efficiencies in two structurally quite similar cylindrical series-parallel planetary gear systems (PGSs) were performed in three separate parts of this paper. Each of these single degree of freedom (DoF) systems consists of three different 2KH subsystems connected in series-parallel. The main goal was to prove that apart from complex, structurally and dynamically coupled PGSs, there are also complex and only structurally coupled PGSs, in which the phenomenon of power flow circulation inside closed loops does not occur. Such a half-coupled type of PGS is herein called pseudo-coupled. Therefore, Part I discusses in detail the geometry, kinematics and statics of coupled PGSs in order to determine power flow paths. A comparison of the directions of power flow in both types of PGSs can be made in Part II after determining the power flow paths in the second planetary gear in a similar way. The directions of power flow in both types of PGSs were determined in a relatively simple way, thanks to the distinction between active and passive torques and thus active and passive shafts of individual subsystems. The efficiency comparison made in Part III will show whether power circulation has an influence on the efficiency value, at least in these two types of PGSs.

Keeping the bus voltage within acceptable limits depends on dispatching reactive power. Power quality improves as a result of creating an effective power flow system, which also helps to reduce power loss. Therefore, Optimal Reactive Power Dispatch (ORPD) studies aim at designing appropriate system configurations to enable a reliable operation of power systems. Establishment of such a configuration is handled through control variables in power systems. On the other hand, installing Distributed Generation Unit (DGU) into a power system can have an important effect on power quality and power loss minimization. In this paper, Grey Wolf Optimization (GWO method is applied to ORPD problem for the first time, to find optimal placement of newly installed DGUs at the power system. Active power loss and voltage minimization have been minimized by optimizing the control variables while keeping them within their upper and lower bounds, and by finding the optimal placement of a newly installed DGU in power system. On the basis of IEEE 30 bus and IEEE 118 bus systems, performance of the suggested approach is investigated. A comparison is also performed among the proposed method and some other methods. Test results demonstrate that the resulting configuration contributes to growing the rate of renewable integration to a power system. The results also indicate that the suggested optimization approach applied to ORPD problem has improved power system performance in terms of both on power loss and voltage deviation. The promising results highlight the potential of the GWO algorithm to facilitate the integration of renewable power sources, and its role in promoting sustainable energy solutions.

The environmental issues we are currently facing require long-term prospective efforts for sustainable growth. Renewable energy sources seem to be one of the most practical and efficient alternatives in this regard. Understanding a nation's pattern of energy use and renewable energy production is crucial for developing strategic plans. No previous study has been performed to explore the dynamics of power consumption with the change in renewable energy production on a country-wide scale. In contrast, a number of deep learning algorithms demonstrated acceptable performance while handling sequential data in the era of data-driven predictions. In this study, we developed a scheme to investigate and predict total power consumption and renewable energy production time series for eleven years of data using a Recurrent Neural Network (RNN). The dynamics of the interaction between the total annual power consumption and renewable energy production are investigated through extensive Exploratory Data Analysis (EDA) and a feature engineering framework. The performance of the model is found satisfactory through the comparison of the predicted data with the observed data, visualization of the distribution of the errors and Root Mean Squared Error (RMSE) value of 0.084. Higher performance is achieved through the increase in the number of epochs and hyperparameter tuning. The proposed framework can be used and transferred to investigate the trend of renewable energy production and power consumption and predict the future scenarios for different communities. Incorporation of the cloud-based platform into the proposed pipeline may lead to real-time forecasting.

Presently power control and management play a vigorous role in information technology and power management. Instead of non-renewable power manufacturing, renewable power manufacturing is preferred by every organization for controlling resource consumption, price reduction and efficient power management. Smart grid efficiently satisfies these requirements with the integration of machine learning algorithms. Machine learning algorithms are used in a smart grid for power requirement prediction, power distribution, failure identification etc. The proposed Random Forest-based smart grid system classifies the power grid into different zones like high and low power utilization. The power zones are divided into number of sub-zones and map to random forest branches. The sub-zone and branch mapping process used to identify the quantity of power utilized and the non-utilized in a zone. The non-utilized power quantity and location of power availabilities are identified and distributed the required quantity of power to the requester in a minimal response time and price. The priority power scheduling algorithm collect request from consumer and send the request to producer based on priority. The producer analysed the requester existing power utilization quantity and availability of power for scheduling the power distribution to the requester based on priority. The proposed Random Forest based sustainability and price optimization technique in smart grid experimental results are compared to existing machine learning techniques like SVM, KNN and NB. The proposed random forest-based identification technique identifies the exact location of the power availability, which takes minimal processing time and quick responses to the requestor. Additionally, the smart meter based smart grid technique identifies the faults in short time duration than the conventional energy management technique is also proven in the experimental results.

The work addresses the problem of Power Quality (PQ) metrics (or indexes) suitable for DC grids, encompassing Low and Medium Voltage applications, including electric transports, all-electric ships and aircrafts, electric vehicles, distributed generation and microgrids, modern data centers, etc. The two main pillars on which such PQ indexes are discussed and built are: i) the physical justification, so the electric phenomena affecting DC grids and components (PV panels, fuel cells, capacitors, batteries, etc.), causing e.g. stress of materials, ageing, distortion, grid instability; ii) the existing standardization framework, pointing out desirable coverage and extension, similarity with AC grids standards, but also inconsistencies. The first point is made more clear and usable by a graphical overview of the discussed phenomena. On this basis PQ is interpreted beyond the usual low-frequency range, including thus supraharmonics and common-mode disturbance, and filling the gap with the Electromagnetic Compatibility domain. However, phenomena typical of EMC and electrical safety (such as various types of overvoltages and fast transients) are excluded. Suitable PQ indexes are then reviewed, suggesting integrations and modifications, to cover the relevant phenomena and technological progress, and to better follow the normative exigencies.

The development of small scale hydroelectric power plants in Norway is determined by natural conditions, policies, attitudes and property rights. The owner of the river is the central decision maker. It is he who decides whether he will develop the power plant himself, Whether he wants to enter into a contract with an external investor and let him develop the power plant, whether he will sell his property rights or postpone the decisions. All available choices will involve risk. In order for him to make the best choice he must find the certainty equivalent to each of the choices and choose the one with the highest certainty equivalent. This is the first time the utility theory of John von Neumann and Oskar Morgenstern has been applied to decision makers in the hydro power industry in Norway.

The calculation of power flow in power systems with the presence of harmonics has been properly studied in the scientific literature. However, power flow calculation considering interharmonic components is still an open question. Traditional methods based on the IEEE1459 standard have proven to be valid and accurate only for linear and sinusoidal systems, but have been criticized for non-linear and non-sinusoidal systems because they are not able to explain correctly the current and voltage interactions beyond the active power. This paper proposes the use of a novel mathematical framework called geometric algebra (GA) to study the power flow considering the interaction of current and voltage harmonics and interharmonics. The use of GA enables the precise determination of the direction and magnitude of the total and single active power flow for each component, as well as other power elements related to the non-active power due to cross interaction. Moreover, this paper makes a novel contribution to the definition of interharmonics in geometric algebra space that has not been done before. To test the validity of the method, both linear and non-linear circuits are proposed and solved by applying voltages and currents with harmonic and interharmonic components. The results obtained show that power flow can be analyzed under the prism of the principle of energy conservation (PoCoE) in a way that allows a better understanding of the power spectrum due to the interaction of harmonics and interharmonics of voltage and current.

The research sought to investigate the long term characteristics of wind in the Kisii region (elevation 1710m above sea level, 0.68^oS, 34.79^o E). Wind speeds were analyzed and characterized on short term (per month for a year) and then simulated for long term (ten years) measured hourly series data of daily wind speeds at a height of 10m. The analysis included daily wind data which was grouped into discrete data and then calculated to represent; the mean wind speed, diurnal variations, daily variations as well as the monthly variations. The wind speed frequency distribution at the height 10 m was found to be 2.9ms^-1 with a standard deviation of 1.5. Based on the two month’s data that was extracted from the AcuRite 01024 Wireless Weather Stations with 5-in-1 Weather Sensor experiments set at three sites in the region, averages of wind speeds at hub heights of 10m and 13m were calculated and found to be 1.7m/s, 2.0m/s for Ikobe station, 2.4m/s, 2.8m/s for Kisii University stations, and 1.3m/s, 1.6m/s for Nyamecheo station respectively. Then extrapolation was done to determine average wind speeds at heights (20m, 30m, 50m, and 70m) which were found to be 85.55W/m², 181.75W/m², 470.4W/m² and 879.9W/m² respectively. The wind speed data was used statistically to model a Weibull probability density function and used to determine the power density for Kisii region.

This paper addresses the effects of electric power quality on robotics operation. A general overview is reported to highlight the main characteristics of electric power quality and their effects on a powered system by considering an end-users viewpoint. Then, authors outline the influence of voltage dip effects by focusing at robotic grasping applications. A specific case of study is reported as referring to LARM Hand IV, a three-fingers robotic hand, which has been designed and built at LARM in Cassino. A dedicated test rig has been settled up for generating predefined voltage dips. Experimental tests are carried out for evaluating the effects of different types of voltage dips on the grasping of objects.

This study examines the wind shear coefficient (WSC) values at three coastal wind sites located in the southern region of Balochistan, Pakistan: Pasni, Ormara, and Jiwani. These WSC values were obtained using 10-minute measured wind speed data at heights of 20, 40, and 60 meters above ground level (AGL). Since wind measurements are typically recorded at lower heights due to cost and resource constraints, extrapolation techniques were employed to estimate wind speeds at higher altitudes. However, using a constant WSC value for extrapolation may lead to significant errors between extrapolated and actual wind speed measurements, impacting the energy output of wind turbines. To evaluate the effect of WSC on energy yield, the study employed power curves and frequency distributions for 2MW and 1.5MW wind turbines. Additionally, wind power density was calculated using air density derived from measured air temperature and surface pressure data, covering two years period from November 2016 to August 2018. The overall mean WSC values were found to be 0.076 at Pasni, 0.094 at Jiwani, and 0.053 at Ormara. The study further investigated the seasonal, monthly, and diurnal variations of WSC. For assessing wind resources at a height of 60m, the study utilized Wind Roses, wind power density, and Weibull parameters. Comparing the actual WSC values presented in this paper with those obtained using the 1/7 power law and measured data at 60m AGL, the energy yield from the wind turbines showed reduced output and capacity factor.

The surface behavior of the ZnO-based films could be modulated via a postannealing and ultraviolet (UV) irradiation with different powers and time, respectively. These present results could provide modulate the microstructure related in grain-size distribution and photocatalytic behavior for potential guide in the field of wide bandgap semiconducting oxides. The ZnO films were prepared onto Corning-1737 glass substrates by using radio-frequency magnetron sputtering without supplying oxygen source at room temperature. For the purpose of obtaining modulable grain microstructures, the as-prepared ZnO films (Z0) were treated via a postannealing modification in vacuum furnace at 300°C for 30 minutes after deposition (Z300) accompanied with the adjustable internal stress. The contact angle (CA) value of ZnO film reduced from 95° to 68° was owning to the different grain microstructure accompanied by a change in size variation. In addition, the UV light with different irradiation powers could also be used to improve the hydrophilicity varied from hydrophobic status to superhydrophilic status due to the desirable surface characteristics of the photocatalytic action. In addition, the photocatalytic activity of ZnO film exhibited efficient photodegradation of methylene blue (MB) under UV irradiation, with a chemical reaction constant of 2.93×10-3 min−1. In this present work, we demonstrated that the CA value of the ZnO films not only caused from hydrophobic to hydrophilic status accompanied by a change in grain size combined with internal stress but also induced by the UV light irradiation combined with photocatalytic activity simultaneously. On the other hand, the enhanced surface plasmonic resonance could be observed that is due to couple electron and photon oscillations and can be generated at the interface between a flat, continuous Pt capping nanolayer. This designed structure could also be considered as a Pt electrode pattern onto ZnO (metal Pt/ ceramic ZnO) for multifunctional heterostructured sensors and devices in near future.

Due to the high solar irradiance or energy price, certain regions in the U.S. may reach 100% PV penetration and experience degradation of frequency response greater than the interconnection as a whole. Therefore, in this section, the 100% PV penetration region in each interconnection is simulated to study the local high PV penetration effects. The study was performed by quantifying RoCoF, frequency nadir, and settling frequency at different regional PV penetration levels. The impact of high regional PV penetration on the compliance of grid code on frequency response is also studied.

Heat and power cogeneration plants based on fuel cells are interesting systems for energy- conversion at low environmental impact. Different fuel cells have been proposed, but experimental testing rigs are expensive and the development of commercial systems is time consuming if based on fully experimental activities. Furthermore, tight control of operation of fuel cells is compulsory to avoid damage, which must be based on accurate models, able to predict the cell behaviour and prevent stresses and shut-down. Some selected examples of steady state, dynamic and fluid dynamic modelling of different types of fuel cells are proposed, mainly PEMFC and SOFC type. The general ideas behind the thermodynamic, kinetic and transport description are recalled, with some examples of models derived for single cells, stacks and integrated power co-generation units.

Nacelle-based Doppler wind lidars have shown promising capabilities to assess power performance, detect yaw misalignment or perform feed-forward control. The power curve application requires uncertainty assessment. Traceable measurements and uncertainties of nacelle-based wind lidars can be obtained through a methodology applicable to any type of existing and upcoming nacelle lidar technology. The generic methodology consists in calibrating all the inputs of the wind field reconstruction algorithms of a lidar. These inputs are the line-of-sight velocity and the beam position, provided by the geometry of the scanning trajectory and the lidar inclination. The line-of-sight velocity is calibrated in atmospheric conditions by comparing it to a reference quantity based on classic instrumentation such as cup anemometers and wind vanes. The generic methodology was tested on two commercially developed lidars, one continuous wave and one pulsed systems, and provides consistent calibration results: linear regressions show a difference of ∼ 0.5 % between the lidar-measured and reference line-of-sight velocities. A comprehensive uncertainty procedure propagates the reference uncertainty to the lidar measurements. At a coverage factor of two, the estimated line-of-sight velocity uncertainty ranges from 3.2 % at 3 m s⁻¹ to 1.9 % at 16 m s⁻¹. Most of the line-of-sight velocity uncertainty originates from the reference: the cup anemometer uncertainty accounts for ∼ 90 % of the total uncertainty. The propagation of uncertainties to lidar-reconstructed wind characteristics can use analytical methods in simple cases, which we demonstrate through the example of a two-beam system. The newly developed calibration methodology allows robust evaluation of a nacelle lidar’s performance and uncertainties to be established in order to further be used for various wind turbines’ applications in confidence.

The article presents the results of tests related to failure analysis and finding ways to diagnose used semiconductor elements, among other, in power electronics converter systems on vessels and offshore facilities (drilling and production rigs, wind turbines). Diagnostic relationships were found between the temperature change in the above systems and the signals generated in form of elastic waves of acoustic emission.

Optical current sensors have been developed and improved in recent decades, and their use has been widespread in power systems, including smart grids. Like any measuring instrument or system, the result of its measurements is associated with a measurement uncertainty, which quantifies its precision. This article presents a review of the main uncertainty contributions that affect the quality and performance of optical current sensors.

Considering that traditional energy sources such as fossil fuel are about to deplete during the following decades, governments try to turn to renewable energy. It is commonly known that Greece has a natural advantage of abundant solar energy and wind power due to its geographical location and characteristics.The main focus of this study is to examine how wind energy potential across the Aegean Sea and continental Greece can provide a promising field for investments in Greece, considering the economic crisis, current trends and future perspectives.We firstly focus on current legislation framework considering that laws associated with such types of investment in Greece are very complex and rapidly changing. Furthermore, a case study for a hypothetical investment plan concerning a wind park located in an Aegean island will be presented. RetScreen which is a software made by the Canadian government, will be used as a decision support tool for analyzing the potential investment scenario and a financial report will follow with estimation of the overall cost, depreciation, upcoming benefits, and payback period of the investment.Data analysis concludes that wind parks still prove to be an economically viable investment, although incentives considering the guaranteed price per kwh and faster investment times must be provided by the government.

Since large power transformers are custom-made, and their design process is a labor-intensive task, their design process is split into different parts. In tendering, the price calculation is based on the preliminary design of the transformer. Due to the complexity of this task, it belongs to the most general branch of discrete, non-linear mathematical optimization problems. Most of the published algorithms are using a copper filling factor based winding model to calculate the main dimensions of the transformer during this first, preliminary design step. Therefore, these cost optimization methods are not considering the detailed winding layout and the conductor dimensions. However, the knowledge of the exact conductor dimensions is essential to calculate the thermal behaviour of the windings and make a more accurate stray loss calculation. The paper presents a novel, evolutionary algorithm-based transformer optimization method which can determine the optimal conductor shape for the windings during this examined preliminary design stage. The accuracy of the presented FEM method was tested on an existing transformer design. Then the results of the proposed optimization method have been compared with a validated transformer design optimization algorithm.

The article presents the results of a morpho-physiological assessment of rice samples by the strength of growth, as well as an assessment of the degree of development of the conducting system of the flag leaves of rice plants. The resistance of varieties to flooding is very relevant in the fight against weeds due to the deep layer of water that weeds cannot overcome. Currently, there are no zoned varieties in Russia that would meet these requirements. Therefore, the problem of creating such rice varieties is urgent, as it will reduce production costs, reduce grain losses during harvesting, improve the quality of the products obtained, and also reduce the pesticide load on the ecosystem. As a result of research, a number of studied samples revealed the potential to quickly lengthen the first leaves, overcome a large layer of water and accumulate vegetative mass. As a result of the evaluation of the conducting system of the flag leaf of rice plants, it was found that in plants with the flood resistance gene Sub1A, which stops growth under water, the conductive beams were smaller in comparison with other fast-growing samples with the AG, Sk genes. Consequently, fast-growing samples have bigger sizes of the conducting system as a resistance mechanism.

Increasing distributed generation and intermittency, along with the increasing frequency of extreme weather events, impose a serious challenge for the electric power supply security. Understanding the costs of interruption is vital in terms of enhancing the power system infrastructure and planning the distribution grid. On the other hand, customer rights and demand response techniques are further reasons to study the worth of power reliability. In this paper, the authors make use of directional distance function and shadow pricing method for a case study from Finland. The aim is to calculate the cost of one minute of power interruption from the distribution network operator perspective. The sample consists of 78 distribution network operators from Finland with cost and network information between 2013 and 2015.

The sound power LW of wind turbines (WTs) over the past decades has developed in relation to their electric power P as LW ∝ logP. The spectral distribution of the sound did not change significantly over time. This applies to the average performance of wind turbines, with differences between individual WT types. Because of the expected growth of onshore wind energy, a greater number of people will be living close to wind farms. This sustains the need for sound reduction. Sound reduction measures, such as serrations, reduced tip speed and low noise modes, may counteract the development of higher sound power from ever bigger WTs. To investigate this, the sound production of WT types over the last decades is analysed in relation to their size and electric power and the application of sound reduction measures. The analysis includes the broad band A-weighted and low frequency sound power levels as well as more detailed spectral distributions. Results show that the sound power level of wind turbines above 3 MW on average increases less with size than smaller turbines did. This is due to a lower blade tip speed and the use of sound reducing serrations. The spectral content of wind turbine sound, including the lower frequencies, has not changed significantly.

This paper studies a multihop amplify-and-forward (AF) simultaneous wireless information and power transfer (SWIPT) relaying system. Each relaying node harvests energy using power splitting (PS) scheme from a part of its received signal to amplify and forward the rest the received signal to the next relay. Based on this system model and signal flow, we derived and solved the convex energy minimization problem with optimal PS ratio. The influence of processing cost was then investigated for the AF-SWIPT system with the decode-and-forward SWIPT as benchmark, where AF-SWIPT was found to be superior.

Power converter technologies have become increasingly vital in various applications due to their efficient management of electrical energy. With the growing prominence of renewable energy sources like solar and wind, the high penetration of power electronic converters has been justified. However, ensuring power quality has emerged as a significant challenge for grid-connected power converters. The divergence from the ideal sinusoidal waveform in terms of magnitude and frequency impacts both grid-side currents and voltages. Several studies have proposed solutions to address power quality issues at the load side. The advancement of power converters has been fueled by the development of high-performance microprocessors and the emergence of high-speed switching devices, such as SiC-MOSFETs. This paper focuses on the design of voltage source converters, particularly those based on SiC-MOSFET semiconductor devices. The article presents the design of H-Bridge cells, discusses two-level voltage source converters based on cascade H-Bridge cells in parallel configuration with experimental fault analysis, addresses the seven-level voltage source converters topology, and explores the design and experimental results of the matrix converter. The findings underscore the importance of considering the entire converter design for improved performance at high switching frequencies. The article concludes by summarizing the main outcomes and implications of this research.

This work investigates how to balance the electricity supply and demand in a carbon-neutral northern Europe. Applying a cost-minimizing electricity system model including options to invest in eleven different flexibility measures, cost-efficient combinations of strategies to manage varia-tions are identified. The results of the model are post-processed using a novel method to map the net load before and after flexibility measures are applied to reveal the contribution of each flexi-bility measure. The net load is mapped in the space spanned by the amplitude, duration, and number of occur-rences. The mapping shows that, depending on cost structure, flexibility measures contribute to reduce the net load in three different ways; 1) by reducing variations of long duration but low amplitude, 2) by reducing variations of high amplitude but short duration and low occurrence or 3) by reducing variations of high amplitude, short duration and high occurrence. It is found that cost-efficient variation management is achieved by combining wind and solar power and by combining strategies (1-3) to manage variations. The cost-efficient combination of strategies de-pends on electricity system context where electricity trade, flexible hydrogen and heat production (1) manage the majority of variations in regions with good conditions for wind power while sta-tionary batteries (3) are the main contributors in regions with good conditions for solar power.

Combined systems for power production and thermally activated cooling have a high potential for improving the efficiency and utilisation of thermal systems. In this regard, various configurations have been proposed and are comprehensively reviewed. They are primarily based on absorption systems and the implementation of multiple levels of complexity and flexibility. The configuration of the absorption power and cooling combined cycle proposed herein has wide commercial applicability owing to its simplicity. The configuration of the components is not new. However, the utilisation of aqueous salt solutions, the comparison with ammonia chiller and with absorption power cycles, the focus on parameters that are important for real-life applications, and the comparison of the performances for constant heat input and waste heat recovery are novel. The proposed cycle is also compared with a system based on the organic Rankine cycle and vapour compression cycle. An investigation of its performance proves that the system is suitable for a given range of boundary conditions from a thermodynamic standpoint, as well as in terms of system complexity and technical feasibility. New possibilities with regard to added power production have the potential to improve the economics and promote the use of absorption chiller systems.

High-penetration of Distributed Energy Resources (DER) in low voltage distribution grids, mainly photovoltaics (PV), might lead to overvoltage in the point of common coupling. Volt-VAr is one of the common control functions for DER power converters used to enhance the stability and the reliability of the voltage in the distribution system and, thus, fulfilling the network operator requirements. In this study, a centralized algorithm will provide local Volt-VAr control parameters to each PV inverter, based on the electrical grid characteristics where each equipment is installed. Since accurate information of grid characteristics is typically not available, the parametrization of the electrical grid is done using power meter data in DER location and a voltage sensitivity matrix. The algorithm has different optimization modes to both minimize voltage deviation and line current. In order to validate the effectiveness of the algorithm and its deployment in real infrastructure, it has been tested in an experimental setup with PV emulators in a set of 5-day tests. Volt-VAr control algorithm successfully adapted its parameters based on grid topology and PV inverter characteristics, achieving a voltage reduction up to 25% of the allowed voltage deviation.

The article concerns problems related to the assessment of reactive power in power networks with non-linear, fast-varying loads, such as electric arc furnaces, rolling mill drives, etc. The operation of this type of loads is characterized by the introduction of interharmonic currents (including higher harmonics) into the power supply network and a relatively low power factor. Rapid changes in the RMS value of the current also cause voltage fluctuations and the related phenomenon - flicker. Therefore, there is a need to evaluate the selection of power of compensating devices taking into account the random nature of load changes and the distortion of current and voltage waveforms, in particular interharmonic components, the impact of which has not been fully investigated so far. To analyze the random nature of load changes, autocorrelation functions were used, which allowed for the estimation of the expected values of the arc furnace current distortion coefficient (based on the recorded waveforms). In order to determine the parameters of reactive power compensating devices, and in particular capacitor banks, an autocorrelation function in the exponential-cosine-sine form was used, which meets the conditions of differentiation. The article contains comparative results of calculations of the reactive power of capacitor banks determined using different methods.

This research, which focuses on wave energy generating technology, suggests a brand-new oscillating float-type wave energy conversion system that is appropriate for the offshore wave environment. To accurately model the device, a three-dimensional viscous numerical pool is created based on STAR-CCM+. The array-type power generation device is numerically simulated using theoretical analysis and numerical simulation, and the wave energy power generation device is arranged as double floats in the front and rear rows, representing triangular array type and rectangular array type, respectively. The triangular array type is a superior layout and can make greater use of marine resources, according to this paper's analysis of the hydrodynamic and power generation impacts of the three array types. The findings are meant to serve as a guide for engineering practice.

. (1) Background: The aim of this study was to verify the differences in body composition, power and lower limb muscle strength in futsal players from three competitive levels. (2) Methods: The study involved 68 players (24.26 ± 4.63 years), divided into three competitive levels: elite, sub-elite and amateur. To assess physical condition, we used the Inbody270, the ChronoJump and the Isokinetic Dynamometer and used the non-parametric Kruskal-Wallis test to compare the three independent variables. (3) Results: There were no differences in body composition between the players at the three competitive levels. With regard to lower limb muscle power and strength, the elite group showed, on average, better performance and capabilities, especially when compared to the amateur group, and all groups showed an H/Q ratio &gt; 60%. (4) Conclusions: We conclude that there are not many differences in physical condition between the three competitive levels of futsal, despite the unequal sporting demands between them. However, the elite group has greater power and muscle strength, and both groups showed a high probability of lower limb muscle injury at this stage of the sporting season, alerting sports training professionals to the importance of individualized analysis of physical condition and performance capacity.

Prime numbers are the atoms of mathematics and mathematics is needed to make sense of the real world. Finding the Prime number structure and eventually being able to crack their code is the ultimate goal in what is called Number Theory. From the evolution of species to cryptography, Nature finds help in Prime numbers. One of the most important advances in the study of Prime numbers was the paper by Bernhard Riemann in November 1859 called “Ueber die Anzahl der Primzahlen unter einer gegebenen Grösse” (On the number of primes less than a given quantity). In that paper, Riemann gave a formula for the number of primes less than x in terms the integral of 1/log(x) and the roots (zeros) of the zeta function defined by: Where ζ(z) is a function of a complex variable z that analytically continues the Dirichlet series. Riemann also formulated a conjecture about the location of the zeros of RZF, which fall into two classes: the "trivial zeros" -2, -4, -6, etc., and those whose real part lies between 0 and 1. Riemann's conjecture Riemann hypothesis [RH] was formulated as this: [RH] The real part of every nontrivial zero z* of the RZF is 1/2. Proving the RH is, as of today, one of the most important problems in mathematics. In this paper we will provide a proof of the RH. The proof of the RH will be built following these five parts: PART 1: Description of the RZF PART 2: The C-transformation PART 3: Application of the C-transformation to in Re(z) 0 to obtain ζ(z)=X(z)-Y(z) PART 4: Analysis of the values of z such that X(z)=Y(z), and |X(z)|=|Y(z)|, that equates to ζ(z)=0 Proof that |X(z)|=|Y(z)| only if Re(z)=1/2 Conclude that ζ(z)=0 only if Re(z)=1/2 for Re(z) 0 PART 5: We will also prove that all non-trivial zeros of ζ(z) in the critical line of the form are not distributed randomly. There is a relationship between the values of those zeros and the Harmonic function that leads to an algebraic relationship between any two zeros.

Since the most important constituent of the cost of cryptocurrency production is energy bills, use of illegal electricity in cryptocurrency mining farms is very common. For this reason, many countries prohibit cryptocurrency production or restrict it with some legal regulations. This situation raises the problem of how to detect illicit cryptocurrency mining. Therefore, innovative approaches are needed to detect illicit cryptocurrency mining farms. In this study, it has been shown that unique noise and/or harmonic characteristics of machines producing cryptocurrency can be used to detect illicit cryptocurrency mining farms. The unique harmonic characteristics formed by data centers on neutral line have been detected by field measurements performed. Electricity distribution companies can make risk assessments with this approach by monitoring energy quality data. As a result, the necessary legal permissions can be obtained to investigate suspicious high-risk consumers. Illicit cryptocurrency mining farms can be detected by investigating at high-risk consumer facilities.

This review delves into the critical role of automation and sensor technologies in optimizing parameters for thermal treatments within electricity power generation. The demand for efficient and sustainable power generation has led to a significant reliance on thermal treatments in power plants. However, ensuring precise control over these treatments remains challenging, necessitating the integration of advanced automation and sensor systems. This paper evaluates the pivotal aspects of automation, emphasizing its capacity to streamline operations, enhance safety, and optimize energy efficiency in thermal treatment processes. Additionally, it highlights the indispensable role of sensors in monitoring and regulating crucial parameters such as temperature, pressure, and flow rates. These sensors enable real-time data acquisition, facilitating immediate adjustments to maintain optimal operating conditions and prevent system failures. It explores the recent technological advancements, including machine learning algorithms and IoT integration, which have revolutionized automation and sensor capabilities in thermal treatment control. Incorporating these innovations has significantly improved the precision and adaptability of control systems, resulting in heightened performance and reduced environmental impact. This review underscores the imperative nature of automation and sensor technologies in thermal treatments for electricity power generation, emphasizing their pivotal role in enhancing operational efficiency, ensuring reliability, and advancing sustainability in power generation processes.

Abstract: Currently, thermal power is the largest source of power in the world. Although the impacts of climate change on cooling water sufficiency in thermal power plants have been extensively assessed globally and regionally, their economic consequences have seldom been evaluated. In this study, the Asia-Pacific Integrated Model Computable General Equilibrium model (AIM/CGE) was used to evaluate the economic consequences of projected future cooling water insufficiency on a global basis, which was simulated using the H08 global hydrological model. This approach enabled us to investigate how the physical impacts of climate change on thermal power generation influence economic activities in regions and industrial sectors. To account for the uncertainty of climate change projections, five global climate models and two representative concentration pathways (RCPs 2.6 and 8.5) were used. The ensemble-mean results showed that the global gross domestic product (GDP) loss in 2070–2095 due to cooling water insufficiency in the thermal power sector was −0.21% (−0.12%) in RCP8.5 (RCP2.6). Among the five regions, the largest GDP loss of −0.57% (−0.27%) was observed in the Middle East and Africa. Medium-scale losses of −0.18% (−0.12%) and −0.14% (−0.12%) were found in OECD90 (the member countries of the Organization for Economic Co-operation and Development as of 1990) and Eastern Europe and the Former Soviet Union, respectively. The smallest losses of −0.05% (−0.06%) and −0.09% (−0.08%) were found in Latin America and Asia, respectively. The economic impact of cooling water insufficiency was non-negligible and should be considered as one of the threats induced by climate change.

Failures in hydraulic systems in offshore wind turbines represent an enormous challenge for manufacturers and operators, as the pitch system statistically is one of the subsystems contributing the most to the downtime of the turbines, which is the case for both electrical and hydraulic pitch systems. However, the complex failure mechanisms of the various different hydraulic components mean that, typically, the critical components of hydraulic systems must be tested to better understand the failure mechanisms. Nonetheless, conventional testing procedures are lengthy and costly. Accelerated testing plays a critical role as it can mimic hydraulic system failure mechanisms in a shorter period. However, the lack of standardized test methods and detailed knowledge about the failure-accelerating effects complicates the process. Therefore, this paper offers a comprehensive examination of approaches applicable to conducting accelerated tests on hydraulic systems. It identifies and discusses five primary component types or sub-components related to the acceleration of testing in hydraulic systems being: pumps, cylinders, seals, valves, and hoses. Each section references studies that delve into accelerated testing methodologies for these individual components. Furthermore, within each component, a concise overview of the current techniques is provided, followed by a discussion and summary based on the state of the art.

Bond Properties were performed on Ag-2.35Au-0.7Pd-0.2Pt-0.1Cu alloy wire with a diameter of 25 µm under different process parameters. Effects of electrical flaming off (EFO) current and EFO time on deformability of the free air ball (FAB) were investigated using scanning electron microscopy (SEM) as well as the effects of ultrasonic power and bonding force on the bond characteristic. The experimental results showed that, FAB grows from a preheated tip to a small ball, a regular ball and finally to a golf ball with increasing either the EFO current or the EFO time, and the FAB presented optimal shape at 25 mA and 650 μs. Moreover, a nonlinear relationship between FAB diameter and EFO time is obtained at the EFO current of 25 mA, which could be expressed by a cubic equation. Further, at a constant bonding force, as the ultrasonic power increased, the mashed ball diameter grew larger and larger, the capillary hole imprint became more and more obvious, and the tail width also increased larger and larger, and vice versa. The optimal ultrasonic power and bonding force are 70 mW and of 45 gf for ball bond and 90 mW and 75 gf for wedge bond, respectively. Finally, for all the bonded wire samples prepared under optimal process parameters, no ball and wedge bond lifts happened after destructive pull test, and full intermetallic compound coverage with perfect morphology occurred on the bond pad after ball shear test, which meant that the bonded wire samples have high bond strength, and hence improved the reliability of microelectronic products.

This paper proposes an approach to estimate the parameters of an AC-DC boost power factor corrector converter which includes an EMI filter. To this end, once the topology is known, measurements at the input and output terminals of the converter are done to identify the values of the passive elements. The proposed methodology is based on the trust-region nonlinear least squares algorithm to identify the parameters of the converter. The steady-state and the transient signals of the converter at the input/output terminals are acquired non-intrusively without any internal modification of the circuitry. The accuracy of the parameter identification carried out is determined by comparing the estimated values with the actual values provided by the manufacturer, and by contrasting the measured signals with the ones obtained with a simulation model with the estimated values of the parameters. The results presented in this paper prove the accuracy of the proposed approach, which can be extended to other power converters and filters.

In 2015, the new installed capacity of global renewable energy power generation exceeded the newly installed capacity of conventional energy power generation, marking a structural change in the construction of the global power system. With the continuous improvement of wind energy utilization technology, the global wind power industry has developed rapidly in recent years. The world's available wind energy is 20 billion kilowatts and has become one of the most economical green power. In China, wind power has become the third largest source of electricity, with the installed capacity increasing from 3.1% in 2010 to 9.2% in 2017. In 2017, China's new installed capacity was 19,660 MW, accounting for 37.45% of the world's new installed capacity. This paper evaluates and compares the efficiency of wind power industry in the four regions of eastern, central, western and northeastern China through EBM models based on radial and non-radial factors. This paper discusses the contribution of China's wind power industry to CO2 emission reduction from the relationship between installed capacity efficiency and CO2 emission reduction efficiency. The conclusions show that the overall efficiency score and ranking of wind power in 2013-2017 is the best in the eastern region, followed by the northeast region and the western and central regions.

Plasma generation by means of electrical discharge requires specialized power supply systems. The applicability of plasma for various plasma processes depends on its parameters, and these in turn depend on the parameters of the power supply systems. Arc plasma can be unstable, generating a lot of electromagnetic interference and overvoltage and overcurrent. The power system of a plasma reactor must guarantee good plasma control characteristics, be immune to disturbances and ensure good cooperation with the power grid. The article analyzes the cooperation of a three-phase plasma reactor, with gliding arc discharge, with a power supply system of a new type. This system integrates an AC/DC/AC converter with a five-column transformer of special design in a single device. Using the properties of magnetic circuits, it was possible to integrate the functions of ignition and sustaining the burning of the discharge in the reactor in a single transformer. Proper design of the transformer is crucial to achieve good cooperation of the AC/DC/AC converter with both the plasma reactor and the power supply network. The presented power supply design shows a number of positive features predisposing it to powering arc plasma reactors.

Low-frequency audible noise generated by the magnetostriction effect inherent to the operation of power transformers has become a major drawback, especially in cases where the electrical substation is located in urban areas subject to strict environmental regulations that imposes sound pressure limits, differing for day and night periods. Such regulations apply a +5 dB penalty if a tonal component of noise is present, which is clearly the case of magnetostriction noise, typically concentrated at twice the industrial frequency (50 Hz or 60 Hz, depending on the country). The strategy used to eliminate the tonal characteristics, therefore contributing to establish compliance with the applicable regulation and to alleviate the discomfort it causes to the human ear, consisted in superimposing to the substation noise a masking sound synthesized from “sounds of nature” with suitable intensities, to flatten the noise spectrum while enhancing the soundscape. The masking system (heavy-duty speakers powered by a microprocessor platform) was validated at an already judicialized urban scenario. Measurement results confirmed that the masking solution was capable of flattening the tonal frequencies, whose beneficial effect yielded the cancellation of the public civil action filed by the neighbors. The proposed solution is ready to be replicated to other scenarios.

Climate change is one of the main issues that humanity is currently facing due to carbon dioxide emissions caused by the use of fossil fuels. Organic Rankine cycles may play an important role in reducing these emissions since they can be operated by using industrial waste heat of renewable energies. The present study presents a comprehensive bibliographic review of organic Rankine cycles. The study not only actualizes previous reviews that mainly focused on basic cycles operating on subcritical or supercritical conditions but also includes the analysis of novel cycles such as two-stage and hybrid cycles and the used fluids. Recuperative and regenerative cycles are more efficient than reheated and basic single-stage cycles. The use of two-stage cycles makes it possible to achieve higher thermal efficiencies and net power outputs of up to 20% and 44%, respectively, compared with those obtained with single-stage cycles. Theoretical studies show that hybrid systems, including Brayton and organic Rankine cycles, are the most efficient; however, they require very high temperatures to operate. Most organic Rankine cycle plants produce net power outputs from 1 kW up to several tens of kW, mainly using microturbines and plate heat exchangers.

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

Face milling is a well known commercial process highly used in heavy industries that consumes high amount of power. Besides power issue, modern manufacturing industries are aiming for per part cost reduction keeping the product quality unimpaired. Unexpectedly if the part is rejected in any stage of manufacturing, the cost of manufacturing dramatically increases. Major cause of part rejection is excessive tool wear that imparts poor surface profile or catastrophic tool failure that causes adherence of broken tool debris onto machined surface. Furthermore, the tool wear is associated with sliding distance (frictional distance) and the tool life quantifies the cost of tools. As such, from the perspective of manufacturing industries it is imperative to optimize the surface quality parameter, cost of part, power consumption, and material removal – this is exactly what is accomplished here. By this work, it is possible to conserve power consumption, produce parts with lower cost, manufacture with uncompromising surface quality and enhanced material removal rate. Moreover, as intermediate factors of interest, the influences of sliding distance, tool life and tool flank wear on the overall machining performance are evaluated. The multi-objective optimization by Grey Relational Analysis (GRA) revealed that for improved product performance and fast manufacturing (case 1) optimum results are: feed per tooth fz = 0.25 mm/tooth, cutting speed vc = 392.6 m/min and cutting length l = 0.5 mm; for resource conservation (case 2) the optimum results are: feed per tooth fz = 0.125 mm/tooth, cutting speed vc = 392.6 m/min, cutting length l = 0.5 mm.

Synchronization is a prerequisite for the stability of electrical energy, which is the cornerstone of a functioning society. Identifying whether generators are synchronized or not has been attracting immense research interest. Utilizing synchronized stability boundaries can strongly simplify stability discrimination. However, fundamental issues such as determining accurate stability boundaries remain challenging. In this study, an accurate synchronized stability boundary equation that is independent of the system and disturbances is presented, and it is applicable to an arbitrarily coupled grid. The special structure induced by spontaneous synchronization appears to be only near the stability boundary. The results of this study show that: the synchronous stability boundary is an intrinsic property of the system, independent of its structure and parameters. Synchronization on the network may be independent of the network. These conclusions will challenge the traditional perception of synchronization on networks, and the synchronization stability of the grid can be analyzed in a uniform way.

Geothermal energy is likely to be a significant contributor in achieving sustainable energy goals and net-zero emissions targets. Within geothermal power plants, heat exchangers play a critical role in harnessing this renewable energy source. However, these heat exchangers encounter significant challenges when exposed to geothermal fluids, including erosion, corrosion, and scaling, which adversely affects their performance and longevity. The current review focuses on surface engineering techniques, particularly coatings, as a highly effective and economically viable solution to address these challenges in geothermal heat exchangers. The review begins by providing an overview of geothermal energy, its significance in the context of sustainability and the important role played by heat exchangers in geothermal power generation, followed by the challenges and their impact on heat exchangers. The subsequent section focuses on surface engineering by coatings and its types employed to enhance the performance of heat exchangers. In the final part, the reader is presented with an overview of the challenges associated with the application of coatings in geothermal heat exchangers and potential future directions in this field. This review offers a detailed understanding of the critical role coatings play in improving the efficiency and service life of heat exchangers in geothermal power plants.

In the field of delta-sigma modulators, reducing system power consumption without sacrificing accuracy has become a challenge. The summing circuit, as the main part of the cascade-of-integrator-in-feedforward delta-sigma modulator, consumes a significant amount of power in active summing. On the other hand, passive summing circuits have low power consumption but can cause attenuation in the summing results. This article proposes a low-power multi-bit delta-sigma modulator based on passive and attenuationless summation scheme. The summation circuit achieves multiplication of the voltage signal carried on the summation capacitor through bidirectional sampling technique, compensating for the inherent attenuation caused by passive summation, thus eliminating the need for active OTA to achieve perfect summation. A 2-order delta-sigma modulator based on 4-bit 1-order passive noise-shaping (NS) SAR quantizer is designed to verify the scheme. By combining a passive NS SAR as the 4-bit quantizer and the third-stage integrator of the system, and incorporating an energy-efficient cascode floating inverter amplifier (FIA) structure as the core active OTA, these elements have significantly enhanced the energy-efficiency of the modulator. Simulation results show that at a supply voltage of 1.2 V and a bandwidth of 20 kHz, the SNDR reaches 102.62 dB, power consumption is only 148.32 μW, and Schreier figure-of-merit (FoM) of SNDR is 183.92 dB.

Methane is the main cause of sewer explosion accidents, and the available monitoring methods mainly use portable gas sensors for on-site detection. However, these methods cannot grasp the dynamic changes in methane in a sewer in real time or make better predictions of methane explosion accidents. Here, we present a low-power online monitoring system for sewer methane in order to ensure the safety of urban sewers. A low-power ultrasonic gas sensor was used to monitor the methane content in biogas. Due to the impacts of changes in CO2, temperature, and humidity in the sewer on the ultrasonic methane measurement results, a corresponding compensation method was proposed. The effectiveness of the compensation method was verified through experiments, which measured the methane concentration under different influences, and the methane values measured before and after compensation were compared. The power consumption was only 1.28 mW if the system worked in intermittent operation mode, and it could operate for about 1.5 years by selecting a lithium battery with a capacity of 5 A · H. The experimental results showed that the gas detection accuracy could meet the commercial requirements and had a high compensation for the impacts of carbon dioxide, temperature, and humidity.

Fossil fuels are non-renewable sources of energy, used particularly in developing countries. There are insufficient fossil fuels and their availability is gradually declining. This leads to a steady increase in prices. Renewable energy is clean, cost-effective and limitless. The considerable population growth and industrial growth have made the construction of solar power plants essential in developing countries. The study used Boolean logical-AHP techniques to select a suitable site for solar power in Duhok Governorate. The result indicated that 68.5% of the area in the governorate of Duhok is available for solar power station construction, especially the most appropriate zone which has 132.2 sq. km and can provide more than 8000 megawatts of solar energy. Most of the appropriate areas are in the south and southwest regions of the governorate, located mostly in the districts of Bardarash, Shekhan and Semel, situated between the major cities of Mosul, Erbil and Duhok. These locations can supply a significant amount of clean, renewable energy for these areas.

History is often thought to be dull and boring – where large numbers of facts are memorized for passing exams. But the past informs the present and future, especially in delineating the context surrounding specific events that, in turn, help provide a deeper understanding of their causes and implications. Scientific progress (whether incremental or breakthroughs) is built upon prior work. Chronological examination of computational chemistry’s evolution reveals the existence of major “epochs” (e.g., transition from semi-empirical methods to first principles calculations), and the centrality of key ideas (e.g., Schrodinger equation and Born Oppenheimer approximation) in potentiating progress in the field. The longstanding question of whether computing power (both capacity and speed) or theoretical insights play a more important role in advancing computational chemistry was examined by taking into account the field’s development holistically. Specifically, availability of large amount of computing power at declining cost, and advent of graphics processing unit (GPU) powered parallel computing are enabling tools for solving hitherto intractable problems. On the other hand, this essay argues (using Born Oppenheimer approximation as an example) that theoretical insights’ role in unlocking problems through simple (but insightful) assumptions is often overlooked. Collectively, the essay should be useful as a primer for appreciating major development periods in computational chemistry, from which counterfactual questions illuminate the relative importance of theoretical insights and advances in computer science in moving the field forward.

This work aims to study and analyze a hybrid power system for electric vehicles consisting of a dual low and high-rate lithium battery block and a fuel cell. In this configuration, the high-rate lithium battery powers the electric vehicle in high power demand processes like acceleration mode or on an uphill road; the low-rate battery operates at a low output power range, servicing the auxiliary systems and low power loads and the fuel cell supplies energy at intermediate power demand conditions, normal driving mode, constant velocity, or flat and downhill terrain. The dual power system improves global efficiency since every power unit operates optimally depending on driving conditions. Power sharing optimizes the lithium battery performance and fuel cell capacity, minimizing the size and weight of each energy system and enlarging the driving range. A comparative study between different lithium battery configurations and fuel cell shows an efficiency improvement of 31.4% for the hybrid dual battery block and fuel cell operating in low, high, and intermediate output power ranges, respectively. The study bases on a simulation process recreating current driving conditions for electric cars in urban, peripheral, and intercity routes. An alternative solution consisting of a hybrid system, fuel cell and a high rate lithium battery produces a 29 % power gain.

Neutral beam injection (NBI) is used for thermonuclear plasma heating, non-inductive current drive, rotation, operation scenario control, and for plasma diagnostics in nuclear fusion devices. NBI is the main source of fast particles in plasma which transmit energy to thermal plasma during their slow-down. Steady-state tokamak operation is only possible when the sub-thermal particles energy is absorbed and effectively confined in plasma volume. While NBI purposes and applications vary through different fusion systems, the engineering tasks performed during research and development (R&D) stage of neutral beamline design have much in common. The NBI studies, especially addressing long pulse and high-power operation typically include a beam transmission analysis and power loads distribution at the structural components of the beamline. Thermo-structural analysis is applied next to heat removal circuits design. ‘Beam Transmission’ (BTR) code is a dedicated tool, developed by a physicist and used by NBI physicists and engineers. BTR was created and 1^st applied during R&D phase of the world’s largest tokamak ITER. BTR code is intended for public usage and routinely applied for detailed simulations of neutral beam propagation through complex beamlines. BTR is flexible and intuitive in input, user-friendly and fully interactive. Thanks to visualization and high performance BTR looks and feels like a real NB flight simulator. Despite BTR ‘mature’ age, the code is still in evolution. Support is available to all new BTR users.

In manual maintenance inspections of large-scaled photovoltaic (PV) or rooftop PV systems, several days are required to survey the entire PV field. To improve reliability and shorten the amount of time involved, this study proposes an electrical examination based method for locating multiple faults in the PV array. The maximum power point tracking (MPPT) algorithm is used to estimate the maximum power of each PV panel; this is then compared with metering the output power of PV array. Power degradation indexes are parameterized to quantify the degradation between maximum power and metered output power. Bidirectional hetero-associative memory (BHAM) networks are then used to locate multiple faults within the entire PV field. For a rooftop PV system with two strings, as seen in Figure 1, experimental results demonstrate that the proposed model has computational efficiency for real-time applications and that its algorithm is easily implemented in a mobile intelligent vehicle.

The vision of the community around Geothermal Power Plant (GPP) is the development of GPP should be based on sustainable development principles, without jeopardizing the quality of life and justice for communities surrounding the power plant. This research aims to: (i) identifying issues that arise as an impact of the development of GPP in the rural Tompaso, and (ii) finding solutions to the issues to minimize the conflict that arises from further GPP development in rural Tompaso and its surroundings. This study is based on the competitive intelligence (CI) research method. The results show that the development of GPP in Tompaso has a negative impact on the natural environment and social environment. The technical solutions offered include: (i) bioremediation by cultivating plants that absorb arsenic; (ii) biosulfurization and desulfurization for reducing air pollution, especially sulfur; (iii ) floods and extreme drought are managed by improving infrastructure and reforestation; (iv) social conflicts (land acquisition, working days, labor recruitment and settlement security) are solved by intensifying program dissemination to the community and involving local communities in decision making. The recommended policy is providing incentives to the local community through strategic programs for the development of human and natural resources.

In this study an adjusting post-processing approach is implemented for improving intra-hourly forecasts of solar power and ramp events of PV solar power systems at different locations in the United States. This study also serves as an out-of-sample test to evaluate the performance of the adjusting approach with different locations and timescales. Thus, various individual intra-hourly forecasts of solar power are combined and adjusted by applying the adjusting approach. Both point and probabilistic forecasts of solar power are included. After that, solar power ramp event forecasting by the adjusting approach is carried out.

Researchers have focused on collaborative governance as an effective measure to realise sustainable natural resource management through the participation of various stakeholders. However, the literature has indicated that issues such as power imbalances tend to undermine the effectiveness of collaborative governance. Powerful actors represented by the government tend to control collaborative processes and produce benefits for dominant groups, while less empowered local communities are often deprived of opportunities for livelihood improvement. Although numerous researchers have analysed the key factors that influence the processes and outcomes of collaborative governance, few have identified a concrete measure to reduce the risk of failure, particularly when managing power imbalances in developing countries. This study explored a methodology to address the power imbalances in collaborative governance based on a case study of a participatory peatland fire prevention project implemented in West Kalimantan Province, Indonesia. Semi-structured interviews and questionnaire surveys conducted with project participants suggested that measures such as establishing a joint team of government officers and villagers, providing a common facilitation training programme, training villagers as facilitators, promoting equal knowledge sharing, and allowing villagers to make their own decisions mitigated the power imbalances between the two groups.

Abstract: The COVID-19 pandemic has disrupted global energy markets and caused significant socio-economic impacts worldwide. The pandemic has also impacted the energy sector, with demand for energy reducing due to lockdowns and reduced economic activity. Hence, this paper aims to provide a comprehensive and analytical review of the impact of COVID-19 on the energy sector and discuss the potential role of artificial intelligence (AI) in mitigating some of these effects. This review examines the changes in energy demand patterns resulting from the pandemic and the implications for the energy industry, including the shifts in policymaking, communication, digital technology, energy conversion, environmental, energy market, and power system operation. The analysis of the energy pattern is discussed according to the timeframes which include pre-, mid-, and post-pandemic periods. Furthermore, we explore how AI can be used to improve energy efficiency, optimize energy use, and reduce energy wastages. The potential for AI to contribute to developing more efficient and sustainable energy systems has also been addressed. Lastly, we highlighted AI’s challenges, which play a significant role in the energy sector's response to the COVID-19 pandemic. The recommendations for AI applications in the energy sector for the transition to a more sustainable energy future are outlined. Information corroborated in this review is expected to provide important guidelines for crafting future research areas and directions in preparing the energy sector for any unforeseen circumstances or pandemic-like situations.

We point out that field equations of general relativity are implied by a maximal force given by c⁴/4G, analogous to the way that special relativity is implied by a maximal speed given by c. We present some of the arguments for this equivalence. The maxi-mal force naturally plays the role of an elastic constant for space-time. Implications of the maximal force for gravitational wave measurements, cosmology and black holes are highlighted. Quantum aspects of the maximal force are discussed.

The high penetration of intermittence resources in the energy market accelerates significantly the decarbonization process but, on the other hand, the electrical system has to face the problem of unbalances. Renewable Energies Sources (RES) are hard to precisely forecast, and power plants are not able to predict the amount of energy that they can provide far from the real time delivery. In this frame, the intraday market gets a fundamental role allowing agents to adjust their position close to the delivery time. In this work we suggest an agent-based model of intraday market combined with genetics algorithms to understand what the best strategy could be adopted by players in order to optimize the market efficiency in terms of welfare and unsold quantity. In the first part we show the effect on the market prices of different scenarios in which players aim at maximizing their revenues and selling/buying all their volumes. In the second part we show the effect of a particular genetic algorithm on the model, focusing on how agents can adapt their strategy to enhance the market efficiency. Comparative analyses are also performed to investigate how the welfare of the system increases as well as the unsold quantity decrease when genetic algorithm is introduced

The environmental impact and associated health issues have been seen as a significant global challenge. Efforts have been made to make solar cookers efficient to reduce the health risk and environmental impact of traditional cooking energy supplies used in rural areas. The solar cookers effectiveness for cooking purposes must be assessed in a specific area before installation. In essence, this paper assesses the experimental efficiency of German Scheffler, small mirror pieces, and aluminum foil based solar cookers. The solar cookers performances are evaluated at international standards by analyzing the figure of merits such as standard cooking power, sensible heating time, and exergy efficiency by using 1.7652 kg water and 1-liter oil as a heating material. The regression analysis is also performed to observe experimental data compliance with regression line. The time required to attain a water temperature of 95˚C by German Scheffler and small mirror pieces is 25 min and 1 hour with their exergy efficiency of 48.51% and 19.16% respectively, while the aluminum foil solar cooker achieves maximum water temperature of 74˚C within 2 hours and 5 minutes with 13.47% exergy efficiency. Similarly, the highest oil temperature of 275˚C is observed for the German Scheffler solar cooker. From experimental and regression results, it is revealed that German Scheffler possesses more cooking power relative to other solar cookers and their performances are highly dependent on following factors such as solar radiations, ambient temperature, environment (dust particles concentration and wind speed), radiation reflective material, aperture area, and heat losses respectively.

In this paper, the current technologies of the regenerative shock absorber systems have been categorized and evaluated. Three drive modes of the regenerative shock absorber systems, namely the direct drive mode, the indirect drive mode and hybrid drive mode are reviewed for their readiness to be implemented. The damping performances of the three different modes are listed and compared. Electrical circuit and control algorithms have also been evaluated to maximize the power output and to deliver the premium ride comfort and handling performance. Different types of parameterized road excitations have been applied to vehicle suspension systems to investigate the performance of the regenerative shock absorbers including that of the nonlinear regenerative shock absorber. The research gaps for comparison of the different drive modes and the nonlinearity analysis of the regenerative shock absorbers are identified and, the corresponding research questions have been proposed for future work.

This article presents the suitability analysis of onshore wind farm sites using an AHP (Hierarchical Analysis Process) multi-criteria decision-making (MCDM) approach based on geographic information system modeling (GIS). This analysis is based on different technical aspects (wind speed, elevation, slope), economic (proximity to the electricity network, proximity to roads) and social (proximity to residential areas, population density). The introduction of the factor “population density” and the constraint “required area” rarely used in previous studies makes it possible to refine the results. The data is classified into several categories in a gradual manner, namely unsuitable (0); less suitable (1); suitable (2); highly suitable (3) and most suitable (4). The results of the study show us that the largest percentage relating to spatial coverage is observed in the “suitable” range with 50.89% and the corresponding TWPP (theoretical wind power potential) is 1377.926 GW; it is followed by “highly suitable” 5.67% and a TWPP of 153.652 GW; then “less suitable” with 1.04% and a TWPP of 28.163GW. No areas were identified in “most suitable” and finally the “unsuitable” range with 42.4%. The results show that the most favorable areas are located in the part of the far north of the country corresponding to the strong wind zone. The sensitivity analysis was carried out based on scenario tests (technical, economic and equal-weight) in order to give greater visibility of choice to the different stakeholders who would like to invest in onshore wind energy in Cameroon. This study is useful in more than one way because the results obtained can help investors, the government and other stakeholders to identify potential areas for the deployment of wind energy systems in Cameroon. Furthermore, a study of hybrid solar-wind systems could improve the efficiency of electricity parks in Cameroon.

Many engineering systems are described by using differential models whose solutions, generally obtained after discretization, can exhibit a noticeable deviation with respect to the response of the physical systems that those models are expected to represent. In those circumstances one possibility consists of enriching the model in order to reproduce the physical system behavior. The present paper considers a dynamical system, and proposes enriching the model solution by learning the dynamical model of the gap between the system response and the model-based prediction, while ensuring that the time integration of the learnt model remains stable. The proposed methodology is applied on the simulation of the top-oil temperature evolution of a power transformer, whose data is provided by RTE, the French Electricity Transmission System Operator.

The purpose of this article is to simulate data transmission and calculate traffic parameters in SAGIN air segment for which Ad Hoc network of flying drones is considered as a model. Traffic modeling is based on the manet-routing-compare example from the ns3 simulator library, which has been supplemented with the code for calculation packet losses, throughput/goodput, and message transmission delays. The program allowed considering drones movement at both low and high speeds from 3.6 km/h to 72 km/h. The dependences of traffic losses on data transmission power, transaction sizes and data transmission rate are obtained and analyzed. The distribution of the average effective arrival rate λ and the throughput/goodput for drones has been studied. Comparing traffic characteristics in models with different numbers of drones allows judging how the required quality of service can be achieved by choosing the right transmission parameters.

The differential gear train and speed regulating motor constitute the variable ratio transmission for grid-connected wind turbine with differential speed regulation. The synchronous generator in the system can accessing the power grid without frequency converter. The transmission can realize the mode of variable speed constant frequency that the wind rotor speed is varying and the generator rotor speed is constant. The power control method is studied under the different wind speed which is lower or higher than rated wind speed with using the relational expression of utilization rate of wind energy Cp, pitch angle β and the tip speed ratio λ. The SIMULINK software is used to build the 1500 kW wind turbine model with differential speed regulation. Some different wind speed is made as input. The feasibility of power control method for grid-connected wind turbine with differential speed regulation is verified by the comparison between the simulation results and the theoretical value of the key parameters.

The extrusion of food for human and animal consumption is a unit operation that includes mixing, shearing and force to the materials related to the rheological properties of the materials in the extruder. The present work aims to study the rheological behavior of an extruded fish diet incorporating hydrolyzed protein flour processed by extrusion. The measurement was carried out online with a slit die rheometer, defining the rheological models and parameters that fit the process. During the extrusion process, the raw materials used were hydrolyzed protein meal, fish meal and cassava starch. For the results, the evaluated treatments were adjusted to the Power Law, where an increase in the shear rate decreases the viscosity of the material, corresponding to a pseudoplastic behavior. The incorporation of hydrolyzed protein flour presented a significant effect on the value of n and Klp, increasing the viscosity with the increase in the percentage of inclusion of HPH. The models obtained for the prediction of the viscosity are adjusted to the changes in shear rate, temperature and humidity of the system.