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Summary: This paper first describes the difficulties in providing the required sample sizes for clinical trials that guarantee type 1 and type 2 error control. The required sample sizes obviously depend on the test employed, and in this study we use the so‐called E‐test, which is known to have extremely favourable size properties and higher power than alternatives. To compute exact powers for this test in real time is not currently feasible, so a corpus of pre‐computed exact powers (and sizes) was created, covering sample sizes up to 500. When there are no solutions within the corpus, a novel extrapolation technique is used. Exact size can be computed after the sample sizes have been extracted; however, for the E‐test the exact size is virtually always very close to the nominal target. All the code has been converted into an R‐package, which is available on CRAN and illustrated. [ABSTRACT FROM AUTHOR]

The team sprint (TS) is a three‐lap pursuit and the most revered event in track sprint cycling. The opening lap of the TS is an important determinant to the overall performance. But despite it being the most controlled and repeatable task in track sprint cycling, very little data are available to better understand the performance of the opening lap. The aim of this study was split into three‐parts: part one, to better understand the profile and the indices thought to be determinants of the opening lap of the TS in elite sprint track cyclists. Part two of the study examined all available timing splits (15, 65, 125 and 250 m) from 36 standing‐start laps. Part three of the study examined the peak torque outputs and peak power outputs of different various starts performed over a 3‐month period. The results showed time to 125 m exhibited a near perfect relationship with starter lap performance. Very strong relationships were seen with 15 and 65 m split times and final lap performance. Peak torque of the lead starting leg and peak power output were shown to be highly predictive 15 m, 65 and 125 m performance in training. These data suggested the first 15 m is highly important and predicts a disproportionately high level of final opening lap time performance. Therefore, it is likely that peak power output normalised to system mass and peak torque of lead leg is a strong determinant of overall performance in the TS. Highlights: Peak speed of the opening lap is achieved in the final quarter of the lap.The timing split of the second half of the opening lap can be used as a proxy of peak speed achieved in the opening lap.The first 15 m (6%) and 65 m (26%) of the opening lap in the track cycling team sprint shows a disproportionately high level of predictability of the final time achieved in the opening lap.Peak power output normalised to system mass is a significant predictor in performance for the first 15 and 65 m.Peak power output is underpinned by maximal torque output of the lead leg normalised to body mass which also is a significant predictor of 15 and 65 m performance. [ABSTRACT FROM AUTHOR]

In terms of electric vehicle architectures, the drivetrain offers unprecedented freedom, but it also creates new obstacles in terms of achieving all needs. The architecture of electric vehicles is simplified and adjustable at the component level because they don't have a combustion engine or fuel tank, only an electric motor and a battery. Implementing safe zones within electric vehicles (EVs) to accommodate battery packs necessitates significant adjustments to ensure the secure integration of the battery. A Battery EV, also known as a pure EV, solely relies on rechargeable battery packs as its source of energy, without any additional propulsion system. The Battery Management System (BMS) plays a significant role in maintaining the safety of electric vehicles by controlling the electronics of rechargeable batteries, whether they are individual cells or battery packs. The BMS plays crucial role in protecting both the user and the battery by monitoring and maintaining the cell's operation within safe limits. This research paper focuses on the control of solar‐powered charging for lithium‐ion batteries. An optimized FOPID controller is utilized to maximize power extraction from PV array and efficiently charge the battery. A hybrid optimization model is employed to optimize the gain parameters of the FOPID controller. [ABSTRACT FROM AUTHOR]

In wind energy systems, increasing system efficiency by maximizing the usage of wind speed has become an important issue. In this study, a single-phase grid-connected Maximum Power Point Tracking (MPPT) system that does not use a speed sensor or any motor control algorithm under variable wind speeds is proposed. In the proposed system, a Permanent Magnet Synchronous Generator (PMSG) is chosen as the generator, and a diode rectifier circuit is used at its output. To achieve the necessary DC bus voltage for grid connection at variable speeds, a DC-DC boost converter is included. The system is simplified by not using any motor control techniques and by employing PI and PR controllers for regulation. Additionally, the use of a diode rectifier instead of a controlled rectifier at the PMSG output reduces the system's cost and size. The proposed MPPT system, with a nominal power of 2kW and a bus voltage of 400V, was tested in simulation studies. The results demonstrated the system's performance and accuracy. [ABSTRACT FROM AUTHOR]

In order to maximize the amount of electrical energy generated and ensure effective use, the conventional I-V or V-I characteristics derived from the diode model of photovoltaic (PV) solar panels are important. Unfortunately, these features cannot be extracted using linear equations. The conventional I-V or V-I characteristics requires extremely drawn-out, time-consuming procedures. Many studies focus on calculating maximum power extraction. The analytical solutions to these equations are also nonexistent. Programming on computers can assist in solving the equations. The Akbaba Model was created specifically for the photovoltaic generator (PVG) to address these challenges. The Akbaba Model relies heavily on coefficients A, B, and C in this equation. The diode model serves as the true model in this case, and the coefficients A, B, and C are calculated. Another advantage of this model is that, because its qualities have partially deteriorated with time, the genuine I-V characteristics of the PV panels can be recovered by measuring again. [ABSTRACT FROM AUTHOR]

This article presents a reconfiguration strategy, named the Cheetah Optimization Algorithm (COA), for maximizing power generation in partially shaded solar photovoltaic (PSPV) arrays. The proposed method’s originality aims to mitigate the negative impacts of partial shading, improve the output power of the PV system, and prevent thermal failure of shaded solar panels. The strategy combines efficient maximum power point tracking techniques with suitable photovoltaic system design topologies. The COA is done on the MATLAB platform and is analyzed with the existing methods such as the Wild Horse Optimizer (WHO), Salp Swarm Algorithm and Heap-based Optimizer. The outcome shows the superior performance of the COA in achieving the extraction of maximum power compared to the other methods. Additionally, by comparing the two patterns of partial shading, it is shown that the COA extracts more power than the existing methods and gets to the global power value faster. The COA is compared with existing methods, including WHO, SSA, and HBO. In terms of accuracy, the proposed system achieves the highest value of 0.93, surpassing the accuracy of HBO, WHO, and SSA, which stand at 0.8, 0.9, and 0.9, respectively. The specificity, precision and recall are also reflect the superiority of the proposed system with the values of 0.87, 0.9, and 0.86, respectively, outperforming the existing algorithms in most categories. [ABSTRACT FROM AUTHOR]

Lacrosse players are required to perform multiple sprints and changes of direction over the course of a game. These skills are reliant on the ability to rapidly produce lower-body force to be successful. Currently, little research examining the relationship between specific performance indicators and relative strength within this population exists. The purpose of this study was to investigate relationships between measures of lower-body strength and power to sprinting and change of direction speed (CODS) among male lacrosse players. Archived data for (n= 18) NCAA Division II male lacrosse athletes were used for this analysis. Lower-body strength was assessed using a one-repetition maximum back squat. Power was assessed using a countermovement jump (CMJ), squat jump (SJ), and standing long jump (SLJ). Sprint speed at 10 and 30 yds (i.e., 9.14 and 27.43 m) and CODS (i.e., T-Test (TT) and modified T-Test (MTT) were also assessed. Pearson's correlation was used to determine relationships between lower-body strength and power to sprint speed and CODS. Significant relationships (r = -0.51 - -0.64, p = 0.05) were discovered between all measures of power and CODS, as well as SLJ and sprint speed (r = -0.51; p = 0.05 and -0.67; p =-0.01, respectively). No significant relationships between relative strength and any measures of sprint speed or CODS were discovered. Although relative strength was not directly related to sprint speed or CODS performance, it may indirectly affect these measures based on its relationship to power, and power's relationship to sprint and CODS performance. [ABSTRACT FROM AUTHOR]

Abstract With the development of the economy and society, we are faced with the dual challenges of energy demands and environmental pollution. As one of the important marine renewable energies, wave energy is widely distributed and abundant, and has considerable applications in various fields. Oscillating body wave energy converter (WEC) is most popular among WECs; its energy conversion efficiency is thus one of the key issues for practical large‐scale applications. This article establishes a new model of the float and vibrator under different motion conditions, conducts simulation training, and then solves the displacement and velocity at different times, and finally optimizes the maximum output power and optimal damping coefficient. Simulink calculation is one of the most effective tools including neural networks, which allows us to achieve intelligent training and simulation. The obtained data imply that the maximum output power could be 8.102 W when the corresponding linear damping is 21,000 N s/m and the rotation damping is 95,000 N s/m. The article takes into account the pitching motion of the float, providing a more realistic model and obtaining optimal power absorbing efficiency. The obtained results could be the potential reference data in practically setting up the wave energy conversion systems.

Ocean wave energy is a new type of clean energy. To improve the power generation and wave energy conversion efficiency of the direct-drive wave power generation system, by addressing the issue of large output errors and poor system stability commonly associated with the currently used PID (proportional, integral, and derivative) control methods, this paper proposes a maximum power control method based on BP (back propagation) neural network PID control. Combined with Kalman filtering, this method not only achieves maximum power tracking but also reduces output ripple and tracking error, thereby enhancing the system's control quality. This study uses a permanent magnet linear generator as the power generation device, establishes a system dynamics model, and predicts the main frequency of irregular waves through the Fast Fourier Transform method. It designs a desired current tracking curve that meets the maximum power strategy. On this basis, a comparative analysis of the control accuracy and stability of three control methods is conducted. The simulation results show that the BP neural network PID control method improves power generation and exhibits better accuracy and stability. [ABSTRACT FROM AUTHOR]

With the development of the economy and society, we are faced with the dual challenges of energy demands and environmental pollution. As one of the important marine renewable energies, wave energy is widely distributed and abundant, and has considerable applications in various fields. Oscillating body wave energy converter (WEC) is most popular among WECs; its energy conversion efficiency is thus one of the key issues for practical large‐scale applications. This article establishes a new model of the float and vibrator under different motion conditions, conducts simulation training, and then solves the displacement and velocity at different times, and finally optimizes the maximum output power and optimal damping coefficient. Simulink calculation is one of the most effective tools including neural networks, which allows us to achieve intelligent training and simulation. The obtained data imply that the maximum output power could be 8.102 W when the corresponding linear damping is 21,000 N s/m and the rotation damping is 95,000 N s/m. The article takes into account the pitching motion of the float, providing a more realistic model and obtaining optimal power absorbing efficiency. The obtained results could be the potential reference data in practically setting up the wave energy conversion systems. [ABSTRACT FROM AUTHOR]

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In order to effectively utilize woody biomass, which has a low abundance density, it is necessary to develop a power generation system that can convert it with high efficiency even with a small capacity as less than 2 MW. For electricity generation, it is reasonable to use a small reciprocating engine. In the case of a naturally aspirated spark ignition reciprocating engine (SIRE), the amount of aspirated gas in one cycle is determined almost entirely by the displacement. The thermal efficiency of the SIRE generally increases with the power. Therefore, to improve the thermal efficiency, it is effective to make the low heating value (LHV) of the fuel higher to increase the power of the naturally aspirated SIRE. In this paper, three methods are used to increase the LHV of the bio-syngas: 1) reducing the nitrogen density of the bio-syngas (upgrade bio-syngas), 2) adding hydrogen to the bio-syngas, and 3) adding methane to the bio-syngas. Using these fuels, 1) the conditions for high power, and 2) the costs assumed for each condition, are evaluated through experiments and estimates. The results showed that the upgrade bio-syngas, obtained by gasification with oxygen-enriched air, had the highest power and the best cost-effectiveness.

Marine wave energy is a new type of clean energy. In order to improve the generation power and wave energy conversion efficiency of the direct-drive wave power generation system, a maximum power control method based on fuzzy sliding mode control was proposed. The method aimed at solving the problems of large output ripple and poor system stability of the commonly used proportional-integral-derivative(PID) control method. In addition, the reaching law parameters were adjusted in real time according to the running state. At the same time, while realizing maximum power tracking, the output ripple was weakened; the tracking error was reduced, and the control quality of the system was improved. In this paper, the permanent magnet linear generator was used as the power generation device, and a system dynamics model was established. The main frequency of irregular waves was estimated by fast Fourier transform (FFT), and the expected current tracking curve was designed to meet the maximum power strategy. On this basis, the conventional PID and sliding mode control methods were compared with the proposed fuzzy sliding mode maximum power control method. The results show that the fuzzy sliding mode control method has improved power and shown better accuracy and stability.

In order to improve the recovery and utilization of hot water energy in gas water heater pipes, a self-powered solution is proposed in this study. The proposed solution focuses on improving energy collection efficiency by increasing the heat transfer coefficient of the water flow and tracking the maximum output power of the temperature plate. The design of heat transfer structure, power characteristics of temperature plate and circuit conversion are analyzed. In order to verify the feasibility of the proposed solution, a test device was constructed for physical testing and verification. The experimental results demonstrate the successful implementation of the self-powered gas water heater. The special structure and perturbation method used enable the experimental device to achieve the maximum power output, and the experimental device can continuously provide 300mW output power. This research contributes to the development of energy -efficient and self-powered gas water heater solutions, offering potential benefits for energy saving and sustainable use in the residential sector.

The trouble with a developing national grid is compounded by the fact that the power system supplies power to a vast number of loads which is fed by a number of generating units sometimes far from the load centers. Variations of loads bring about power losses and corresponding increase in the reactive power requirements of the transmission systems. Thus, the paper is aimed at establishing the point of collapse of transmission lines to enable a control system operator to take proactive measures in the event of small/large system disturbances. Voltage collapse proximity indicator is exploited to show that the variations in load close to the maximum load require extremely large amounts of reactive power at the sending end in order to support the increase in load. In the work, it was identified that Katemkpe-Shiroro transmission line is the most critical transmission line contributing immensely for voltage collapse scenarios in Nigeria national grid. Consequently, it ranked first because it has the highest voltage collapse proximity index. Computation involving voltage collapse proximity indicator obtained the collapse point or the knee point as 2.8684. This serves as a criterion that will enable control system expert to take proactive measure before the impending voltage collapse.

In this study, a new multiobjective optimisation-based approach for Wind Farm Layout Optimisation (WFLO) is developed. The proposed approach combines four distinct Evolutionary algorithms (EA) based on multiobjective optimisation methods into a more powerful parallel method. The four combined algorithms are: the Radial Space Division based EA (RSEA), the Reference Points based EA (RPEA), RVEA embedded with the reference vector regeneration strategy (RVEAa) and the Reference Vector Guided EA (RVEA). The proposed approach is PRPSVEAa, where the letter P stands for parallel, and the remaining letters are used from different combined methods. In this research, four case studies have been investigated using four different commercial wind turbines where the hub heights of Wind Turbines (WT) are kept the same in some cases and varied in some. The results indicate that the Pareto set of solutions varies from each other with different numbers of WT as they spread over a wide region. This offers the designer the most suitable layout solution based on technical and economic factors. The obtained result can also be used to plan for future extensions of the research work.

In this article, a maximum Power Point Tracking (MPPT) controller is designed for photovoltaic (PV) applications. This controller has been implemented with Fuzzy Gain Scheduling of Proportional–Integral–Derivative (PID) type controller (FGS-PID). To implement this controller, scaling factors (SF) for the input signals of FGS are applied. The recommended adaptive two-level controller has all the welfare of fuzzy logic system (FLC) and PID control. Zieglere–Nichols technique is used to fine-tune the initial PID's gains. The PID's gains are updated with FGS-PID in transient and steady-state conditions to cope with fluctuations, minimize settling time and ensure stability. FLC is used for gain factors to deal with tuning of conditioned input signals of the FGS-PID. Moreover, FLC and an improved shuffled frog leaping algorithm (ISFLA) are applied to tune the member functions (MFs) of FGS. The use of this algorithm can lead to automatic regulation of the triangular MFs. Simulations are done to confirm the edge of this approach over conventional methods. It is very fast and accurate in tracking the maximum power. It provides minimum oscillations and improved dynamic response than other approaches. The speed of the tracking is also improved with acceptable accuracy. [ABSTRACT FROM AUTHOR]

Photovoltaic (PV) energy has become a considerably more attractive source of power, with costs continually declining. Along with the implementation of this sustainable energy system, the power supply stability should be extensively investigated, particularly in off-grid systems where electricity storage becomes a limitation. The performance of the standalone photovoltaic battery system (SPVBS) is mainly reliant on the DC-bus voltage and its capacitor. The shortcomings of utilizing a small film DC-bus capacitor in SPVBS include the instability and low-frequency ripple of DC-bus voltage and the system's dynamic MPPT techniques performance. Therefore, this study proposes a new technique of regulating the various system components that stabilizes the DC-bus voltage, extracts stable output power despite harsh sudden load and radiation fluctuations, and maintains the system's functionality with or without the battery storage system (BSS). The proposed approach uses a hybrid salp swarm algorithm and particle swarm optimization (SSA-PSO) combined with an intelligent direct sliding mode controller (DSMC) to eliminate the instability and ripples of DC-bus voltages. Moreover, it employs DSMC for bidirectional DC-DC converter and boost converters to enhance the system's dynamic MPPT techniques capabilities. Four different modes are considered according to the energy availability, demand, and battery's state of charge (SOC). Additionally, this easy-to-use technique keeps the DC-bus voltage stable even when the battery storage system is not available. Simulation and experimental results revealed the resilience performance of the proposed intelligent SSA-PSO-DSMC technique in terms of DC-bus regulation, output power extracted, and current harmonics reduction compared to PSO, SSA, cuckoo search optimization (CSO), and grey wolf optimization (GWO). • A novel SSA-PSO-DSMC control is designed for PV converter to achieve MPPT and regulate DC-bus voltage. • The performance of SSA-PSO-DSMC controller was investigated on several stringent and realistic environmental profiles. • SSA-PSO-DSMC improves global MPP tracking speed and dynamic performance. • HIL experiment validates the implementation feasibility. [ABSTRACT FROM AUTHOR]

The effect of the donor impurity concentration and the lifetime of charge carriers in a crystalline silicon substrate on the maximum power of heterojunction thin-film solar cells is studied. The model used in the calculations takes into account the features of photocurrent generation under conditions of medium or high levels of injection of charge carriers at an arbitrary ratio between the diffusion length and the thickness of the semiconductor wafer. The proposed technique makes it possible, with sufficient accuracy for practical purposes, to calculate the permissible variation limits of the substrate parameters, which ensure the specified values of the performance characteristics of photoelectric converters. [ABSTRACT FROM AUTHOR]

In view of the poor effect of battery power tracking control in the current solar power generation system, the maximum power point tracking (MPPT) control method of photovoltaic cell under the influence of shadow is proposed. The MPPT control method of photovoltaic cell is optimized by using the influence of shadow, the structural characteristics of photovoltaic cell are optimized, and the voltage rise and fall DC / DC conversion circuit is adopted, The maximum power identification algorithm of photovoltaic cells is set, and the voltage disturbance method is used to realize the MPPT, so that the solar photovoltaic cells always maintain the maximum power output, so as to ensure the control effect. Finally, the experiment shows that the MPPT control method of photovoltaic cells has high practicability and fully meets the research requirements.

Photovoltaic (PV) has become one of the most important renewable energy sources today. Getting the maximum power from these systems in changing environmental conditions is an important research subject. Maximum power point trackers (MPPT) are used to get the highest efficiency from PV arrays under current irradiance and temperature conditions. Additional hardware such as sensors, partial shading, and complex algorithms are factors affecting MPPT performance. The MPPT method proposed in this study does not require any additional hardware, has a simple algorithm, is easy to implement and can extract maximum power from the PV array even under partial shading conditions. In the proposed method, firstly, the electrical characteristic of the PV array is obtained by emulating the dc-dc converter as a load. The maximum power point of the array was found using the current and voltage data during this process. Subsequently, the PV array was operated at this point and the maximum power was harvested. The proposed method was validated on the Matlab-Simulink environment by simulating various irradiance values.

This work aims to contribute to studies on the geometric optimization of thermoelectric generators (T E G s) through a combination of the reduced variables technique and supervised machine learning. The architecture of the thermoelectric generators studied, one conventional and the other segmented, was determined by calculating the cross-sectional area and length of the legs, and applying reduced variables approximation. With the help of a supervised machine learning algorithm, the values of the thermoelectric properties were predicted, as were those of the maximum electrical power for the other temperature values. This characteristic was an advantage that allowed us to obtain approximate results for the electrical power, adjusting the design of the T E G s when experimental values were not known. The proposed method also made it possible to determine the optimal values of various parameters of the legs, which were the ratio of the cross-sectional areas (A p / A n) , the length of the legs (l) , and the space between the legs (H) . Aspects such as temperature-dependent thermoelectric properties (Seebeck coefficient, electrical resistivity, and thermal conductivity) and the metallic bridge that connects the legs were considered in the calculations for the design of the T E G s , obtaining more realistic models. In the training phase, the algorithm received the parameter (H) and an operating temperature value as input data, to predict the corresponding value of the maximum power produced. This calculation was performed for conventional and segmented systems. Recent advances have opened up the possibility of applying an algorithm for designing conventional and segmented thermocouples based on the reduced variables approach and incorporating a supervised machine learning computational technique. [ABSTRACT FROM AUTHOR]

Partial shading is a significant limitation that decreases the maximum power output of large photovoltaic (PV), and building integrated photovoltaic (BIPV) arrays installed in modern buildings. One of the optimum solutions to mitigate the difficulty related to partial shading is applying different interconnected fixed BIPV array configurations. This research article aims to modelling, simulation, and performance analysis of a novel conventional 7 × 8 Quarter-Tied (QrTd) fixed BIPV array configuration under the centre, left staircase, frame, left corner, diagonal, and left side shading pattern cases in Matlab/Simulink. Moreover, a comprehensive study with existing conventional fixed BIPV array configurations such as Series-Parallel (SePl), Bridge-Linked (BdLk), Honey-Combed (HnCb), Triple-Tied (TrTd), Total-Cross-Tied (TtCrTd) array interconnections is also executed. The variable parameters for performance evaluation include global maximum power point (GlMxPoPt), mismatch losses (MmLs), fill factor (FiFa), efficiency (Effy), relative power loss (RlPwLs) and relative power gained (RlPwGn). Experimental validation under two partial shading cases is also reported for the justification of simulation results. The simulation results infer that the proposed QrTd configuration improves GlMxPoPt by 4.31%, reduces MmLs by 3.54%, and improves FiFa & Effy by 2.44% and 0.34%, respectively, under six different shading cases. The experimental results conclude that the proposed QrTd configuration improves GlMxPoPt by 1.62%, reduces MmLs by 1.15%, and improves FiFa & Effy by 0.65% and 0.14%, respectively, under two shading cases. Moreover, the wiring requirement and the wiring losses are also lower in the proposed QrTd configuration than in the TtCrTd configuration. [ABSTRACT FROM AUTHOR]

The vast usage of electric vehicles (EVs) has raised to minimize the dependency on fossil fuels. The Photovoltaic (PV) is used in the charging station to supply the required power to the EV. Batteries' charging and discharging control have become a major challenge in RES interconnected EV charging stations. To tackle this issue, a novel fractional-order tilt integral derivative controller (NFO-TIDC) is used in the battery-connected bidirectional converter. Moreover, special considerations of the NFO-TIDC are accomplished with an improved Chimp optimization algorithm. In addition, the enhanced seagull optimized maximum power tracking controller has been proposed for maximizing the power from PV under varying irradiance. The proposed method is implemented on MATLAB/Simulink, and the obtained results verify the superiority of the controller. [ABSTRACT FROM AUTHOR]

Ludwig Boltzmann suggested that natural selection was fundamentally a struggle among organisms for available energy. Alfred Lotka argued that organisms that capture and use more energy than their competition will have a selective advantage in the evolutionary process, i.e. the Darwinian notion of evolution was based on a fundamental, generalized energy principle. He extended this general principle from the energetics of a single organism or species to the energetics of entire energy pathways through ecosystems. Howard Odum and Richard Pinkerton, building on Lotka, extended this concept to 'The maximum power principle' and applied it to many biological and physical systems including human economies. We examine this history and how these ideas relate to concepts from other disciplines including philosophy. But there has been considerable confusion in understanding and applying these concepts which we attempt to resolve while providing various examples from routine life and discussing some unresolved issues. This article is part of the theme issue 'Thermodynamics 2.0: Bridging the natural and social sciences (Part 2)'. [ABSTRACT FROM AUTHOR]

Ocean wave energy is a new type of clean energy. To improve the power generation and wave energy conversion efficiency of the direct-drive wave power generation system, by addressing the issue of large output errors and poor system stability commonly associated with the currently used PID (proportional, integral, and derivative) control methods, this paper proposes a maximum power control method based on BP (back propagation) neural network PID control. Combined with Kalman filtering, this method not only achieves maximum power tracking but also reduces output ripple and tracking error, thereby enhancing the system’s control quality. This study uses a permanent magnet linear generator as the power generation device, establishes a system dynamics model, and predicts the main frequency of irregular waves through the Fast Fourier Transform method. It designs a desired current tracking curve that meets the maximum power strategy. On this basis, a comparative analysis of the control accuracy and stability of three control methods is conducted. The simulation results show that the BP neural network PID control method improves power generation and exhibits better accuracy and stability.

Renewable energy generation is a critical component of society's long-term sustainability, and numerous energy sources, including biogas, solar, biomass, and wind, must be fully utilized to satisfy current demands. Different countries are off the grid. This study includes a real-life case study. Researchers created a mathematical optimization technique utilizing a CPLEX analyzer to produce the required solar capacity simultaneously reducing the cost of energy (COE) to match the requirements of this settlement. Various situations were examined in this research about present energy availability, for instance, at varying periods of each year, economic expenses, the feasibility of sources including such biomass and biogas, and the profitability of wind power generation given the related high prices. Lastly, the study investigated the impact of geothermal power generation on carbon dioxide emission. [ABSTRACT FROM AUTHOR]

The effect of temperature is considered a significant factor in controlling the output voltage of the photovoltaic (PV) module. In this work, a numerical analysis with an experimental demonstration were investigated to analyze the temperature effect on the performance of PV module. In the numerical part, the current-voltage I-V and power-voltage P-V curves of the PV module were simulated under the influence of various module temperature ranged from 25 to 65 ℃ as well as various solar radiation from 200 to 1000 W/m2. In addition, the variation of PV output electrical characteristics with a module temperature were performed to analyze the temperature coefficients of the PV module. Moreover, the experimental demonstration was performed to analyze performance of the PV module under the real weather conditions of Iraq. The numerical results conclude that the maximum power was recorded 165 W at 1000 W/m2 solar irradiance and 25 ℃ PV module temperature. Furthermore, the temperature coefficient was recorded a maximum value with output power about (−0.26) %/℃. Besides, the experimental results show that the maximum power was recorded 131.2 W at solar irradiance about 920 W/m2.

This paper proposes an electrical array reconfiguration system depending on the Coronavirus optimization algorithm (CVOA) for reducing the partial shading conditions and increasing its power. The increasing use of fossil fuels to generate energy is causing environmental issues. Therefore, human society moves toward renewable energies, such as wind energy, solar energy, and geothermal energy. Nowadays, solar energy plays a significant role in the energy crisis. In recent years, the photovoltaic (PV) system is used to gain solar energy. But, partial shading is the most significant and prominent one in changing the behavior of PVs. The impact of partial shading reduces the photovoltaic output power and it is overcome by the electrical array reconfiguration. The proposed approach generates a reconfigured array pattern, thus shading property spread over the array and growing the power output. In the reconfiguration method, the physical position of the modules remains constant, but their electric connections are modified depending on the irradiance level. The proposed CVOA approach has been experimented with under dissimilar shading conditions on 6 × 6 sizes of the array and analyzed with TCT and SuDoKu patterns. The efficiency of the CVOA algorithm is higher compared to those of the reconfiguration methods. [ABSTRACT FROM AUTHOR]

This study proposes an approach to obtain maximum power via wireless power transfer using a single primary-side capacitor. It is shown that higher power is achieved when compared to the common wireless power transfer circuit under resonance with dual (primary- and secondary-side) capacitors. This approach is divided into three phases. By choosing the capacitor and frequency as freely assignable variables, we symbolically obtain a formula that allows us to determine the optimized capacitance and frequency for maximum power. To verify our method, we used a numerical analysis and compared it with an electronic circuit simulation. The symbolic formula is able to maintain maximum power despite changes in load or in the coupling coefficients. [ABSTRACT FROM AUTHOR]

Purpose: An a posteriori multicenter reliability study was conducted to compare the reliability of the outcomes derived from the linear force–velocity (F–V) relationship (F-intercept [F0], V-intercept [V0], F–V slope, and maximum power [Pmax]) using a 2-point method based on 2 distant loads with respect to a multiple-point method based on 4 proximal loads and a multiple-point method that considered all 6 tested loads. Method: Data from 63 healthy men derived from 3 studies were analyzed. The F–V relationship obtained from the bench-press-throw exercise was determined in 2 separate sessions using 3 different combinations of loads: 2-point method (20–70% of 1-repetition maximum [1RM]), 4-load multiple-point method (30–40–50–60% of 1RM), and 6-load multiple-point method (20–30–40–50–60–70% of 1RM). Reliability was assessed through the coefficient of variation (CV), whereas a CVratio of 1.15 was deemed as the smallest important ratio. Results: The 2-point method provided the outcomes of the F–V relationship with greater reliability than the 4-load multiple-point method (F0, 3.58% vs 4.53%, CVratio = 1.27; V0, 5.58% vs 7.85%, CVratio = 1.41; F–V slope, 8.57% vs 11.99%, CVratio = 1.40; Pmax, 4.33% vs 4.81%, CVratio = 1.11). The reliability of the 6-load multiple-point method was comparable to the 2-point method (F0, 3.53%, CVratio = 1.01; V0, 5.32%, CVratio = 1.05; F–V slope, 8.38%, CVratio = 1.02; P0, 3.74%, CVratio = 1.16). Conclusion:The distance between experimental points is more important for obtaining a reproducible F–V relationship than the number of experimental points; therefore, the 2-point method could be recommended for a quicker assessment of the F–V relationship. [ABSTRACT FROM AUTHOR]