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There has been a global expansion of solar electricity during the past decades. Solar photovoltaic (PV) electricity generation is not only simple but also environmentally benign and cost-effective. This is the most affordable and suitable power source for rural areas. The PV power output is unavoidably suppressed when there is partial shade. There were numerous maximum power point tracking (MPPT), arrays, and reconfiguration approaches that were available earlier. The authors have previously described an L-shaped propagating array arrangement. The L-shaped configuration creates the PV rows based on the chess game coin. The knight coin of this game will move in the shape of “L,” which inspired new array configurations. This work discusses the hybridization of the L-shaped configuration with the conventional array configurations. The proposed hybrid L-shaped configuration has been developed in MATLAB/Simulink, where the conventional configuration and the hybrid configurations are validated under different test conditions. The test conditions are created based on the all possible real-word shading patterns. The power generation, mismatch losses, and characteristic curves were attained for each method, and this work presents all these validations with the inferences. In addition, the justification for the suitable array configuration with.

The second-generation hybrid and Electric Vehicles are currently leading the paradigm shift in the automobile industry, replacing conventional diesel and gasoline-powered vehicles. The Battery Management System is crucial in these electric vehicles and also essential for renewable energy storage systems. This review paper focuses on batteries and addresses concerns, difficulties, and solutions associated with them. It explores key technologies of Battery Management System, including battery modeling, state estimation, and battery charging. A thorough analysis of numerous battery models, including electric, thermal, and electro-thermal models, is provided in the article. Additionally, it surveys battery state estimations for a charge and health. Furthermore, the different battery charging approaches and optimization methods are discussed. The Battery Management System performs a wide range of tasks, including as monitoring voltage and current, estimating charge and discharge, equalizing and protecting the battery, managing temperature conditions, and managing battery data. It also looks at various cell balancing circuit types, current and voltage stressors, control reliability, power loss, efficiency, as well as their advantages and disadvantages. The paper also discusses research gaps in battery management systems.

Solar photovoltaic (PV) systems are susceptible to power loss caused by environmental factors such as partial shading and temperature changes. To address this issue, PV modules are connected in array configurations. However, these configurations can lead to mismatch losses between the PV rows, which reduce power output. While there are many solutions to mitigate these losses, the performance of each solution can vary depending on the environmental conditions and the array configuration logic. This research paper evaluates the performance of fifteen existing static PV array configuration techniques under various shading patterns. We analyze the mathematical formulation and logic used behind each configuration, as well as the shade dispersion rate, power generation, power losses, advantages, and disadvantages. Our analysis includes a MATLAB/SimulinkⓇ model of a $5\times 5$ array for each configuration under different shading patterns. The performance of consistent and best configurations is also evaluated in a real-time environment. The results categorize each configuration as consistent, best, average, or poor. This paper provides a detailed analysis of the different PV array configurations and their performance, which can help in selecting the optimal configuration for specific environmental conditions.

One of the most critical operations aspects is power management strategies for hybrid AC/DC microgrids. This work presented power management in hybrid AC–DC microgrids with a droop control strategy. At first, photovoltaic, Wind, and battery are used as the power sources, which supply the power with uncertainties. The AC and DC microgrids are controlled by an Adaptive neuro-fuzzy inference system (ANFIS) controller and Proportional Integral Derivative (PID) controller. Simultaneously we calculate the running cost for photovoltaic, Wind, and Battery. Moreover, an optimizer based on the elephant herding optimization algorithm is formulated to reduce the cost price. This method utilizes two stages like clan updating operator and separating operator. This cost value is used to calculate the Droop Coefficients in Droop Control Strategy. The autonomous droop control strategy is utilized in the interlinking converter to share the load between AC and DC. This proposed concept is implemented in the MATLAB tool, and the performance is taken in terms of voltage, power, and current for PV and wind, DC link voltage and load current. The bidirectional ac/dc interlinking converter power flow was subsequently changed from 2.2k W to −2k W. The effectiveness of the power dispatch mode under uniform control has been verified.

Efficiency of photovoltaic (PV) systems is decreased by mismatch losses resulting from uneven panel irradiation. Current compensation techniques that inject compensatory current and measure currents by periodic row short-circuiting are unavoidably blackout-causing. In this work, a novel current compensation technique is presented that dynamically measures and reacts to variations in irradiance using light sensors on each panel. The program compiles these data to determine the overall irradiance of each row and to precisely modify the injected current to sustain output without any interruptions to operation. The proposed approach lowers mismatch losses more effectively than traditional techniques, as demonstrated by MATLAB/Simulink simulations of seven shading patterns. Under center shading, the proposed approach raised system efficiency by 36%. These results indicate a move towards more flexible solar energy solutions by implying that sensor-driven data analytics can increase PV system operational efficiency and reliability.

For WLAN/WIMAX applications, a brand-new tree-shaped metamaterial-loaded microstrip antenna is suggested. The reduced ground plane size and 4.4 dielectric constant (r) and 0.02 loss tangent (δ) dielectric are used to manufacture the 15 × 16 × 1.6 mm3 microstrip antenna. Two X-shaped slots are added to achieve the characteristics needed for WIMAX applications at 5.5 GHz. Additionally, a split-ring resonator is added to the structure to increase its bandwidth. It runs for WLAN applications with a center frequency of 5.8 GHz. The proposed structure’s measured impedance bandwidth is 45.39% with SRR and 53.48% without SRR, respectively. The proposed antenna is capable of satisfying the major requirements of modern wireless devices such as multiband operation, compact size, large bandwidth, and planar structure. The best outcomes are attained with the aid of parametric analysis of feed width, ground height, and slot width. All electromagnetic simulations were performed using CST Studio software. The measured results and the simulation agree. The waveguide extraction approach is used to demonstrate the SRR’s permeability property. The suggested antenna had adequate impedance matching, was small, and had a wide bandwidth.

Partial shading is an unavoidable factor that reduces the performance of solar PV systems. The PV system receives uneven irradiation due to partial shading which causes the mismatch loss. The partial shading distracts the irradiation from the PV modules that makes the healthy modules as idle or low performing modules. The mismatch loss can be mitigated by uniformly distributing the partial shading over the PV array. In this work, L-shaped propagated array configuration method with a new dynamic reconfiguration algorithm have proposed for enhancing the energy conversion under the partial shading conditions. A new kind of array configuration is implemented in a $4\times 4$ PV array for the better shade dispersion. Further, a dynamic reconfiguration algorithm is employed to disperse the effect of partial shading. The combination of new array configuration and reconfiguration method is simulated in MATLAB/Simulink® and implemented in hardware. The outputs are measured under all possible shading patterns and validated with the outputs of convention methods for observing the enhanced energy conversion rate of the proposed system.

Partial shading causes mismatch losses in the solar PV system. In the PV array, the power output from the healthy PV modules is gone in vain due to the mismatch losses. The PV array construction with the high resistivity to the mismatch loss generation is the progressing research work in the research field. In this work, a new kind of array configuration scheme is framed for the PV system for overcoming the effect of partial shading. The proposed array configuration has a high resistivity to the mismatch loss generation over the other conventional array configuration methods. The array configuration is framed in a pattern that is similar to the spiral step pattern. Each row of the PV array is constructed with the PV modules from each row of the conventional Total Cross Tied configuration with the optimized distance. This row construction allows the system to uniformly disperses the partial shading over the PV array. The simulation analysis is carried out by applying various shading patterns in MATLAB/SimulinkⓇ. The performance of the proposed array configuration is also analyzed in the experimental setup and the results were presented.

Low-cost photovoltaic-powered elevators (PVPEs) have gained ever-increasing attention in the last few years for their advantages in terms of renewable energy and low maintenance costs after installation. In this paper, four highstep-up DC-DC converters for low-voltage sources such as solar photovoltaic, fuel cells, and battery banks are proposed. Their performances are evaluated in terms of optimal capability and high reliability. Among the four proposed architectures, the bootstrap converter is selected for its ability to restrict losses and other redundant parameters. The proposed converter drives the inverter-driven switched reluctance motor (SRM) assembly through a directly coupled method, which eliminates the need for battery banks while aiding in cost reduction. The prototype model is implemented, and results are validated, showing promising performance and thus being very efficacious for application to low-cost PVPEs. [ABSTRACT FROM AUTHOR]

The Electric Vehicle (EV) landscape has witnessed unprecedented growth in recent years. The integration of EVs into the grid has increased the demand for power while maintaining the grid's balance and efficiency. Demand Side Management (DSM) plays a pivotal role in this system, ensuring that the grid can accommodate the additional load demand without compromising stability or necessitating costly infrastructure upgrades. In this work, a DSM algorithm has been developed with appropriate objective functions and necessary constraints, including the EV load, distributed generation from Solar Photo Voltaic (PV), and Battery Energy Storage Systems. The objective functions are constructed using various optimization strategies, such as the Bat Optimization Algorithm (BOA), African Vulture Optimization (AVOA), Cuckoo Search Algorithm, Chaotic Harris Hawk Optimization (CHHO), Chaotic-based Interactive Autodidact School (CIAS) algorithm, and Slime Mould Algorithm (SMA). This algorithm-based DSM method is simulated using MATLAB/Simulink in different cases and loads, such as residential and Information Technology (IT) sector loads. The results show that the peak load has been reduced from 4.5 MW to 2.6 MW, and the minimum load has been raised from 0.5 MW to 1.2 MW, successfully reducing the gap between peak and low points. Additionally, the performance of each algorithm was compared in terms of the difference between peak and valley points, computation time, and convergence rate to achieve the best fitness value. [ABSTRACT FROM AUTHOR]