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DC microgrids are getting more attention because majority of the renewable energy sources generate DC output voltage and also modern gadgets require DC voltage for its operation. In this work, high gain SEPIC (HGSC) topology is derived from switched inductor voltage boosting cell (SIVBC). The HGSC converter provides continuous source current due to SIVBC and high conversion ratio and achieves maximum efficiency of 97.88% when compared with the existing SEPIC topology. The operating modes, conversion ratio expression, power loss distribution, voltage drop, current stress of the semiconductor devices, and efficiency are also analysed. In DC microgrids, the HGSC intends to track the peak power from solar PV array. An incremental conductance algorithm is employed to track the peak power of the solar PV modules. The power flow in the microgrid system is analysed by employing synchronous reference frame theory‐based current controller. In order to validate the theoretical concepts of the HGSC converter, the hardware model is developed for the load rating of 1,000 W/380 V output voltage. [ABSTRACT FROM AUTHOR]

Due to their inherent ability and environmentally friendly nature, renewable energy sources are the only real option for producing pollution-free energy in the modern era. Solar energy is one of the best possibilities in this family for supplying civilization with the power and energy it needs. Researchers can efficiently boost a PV panel's efficiency by using the maximum power point tracking (MPPT) approach to extract the most power from the panel and send it to the load. The authors of this study examined and surveyed the sequential advancement of solar PV cell research from one decade to the next, and they elaborated on the upcoming trends and behaviours. Many maximum power point tracking algorithms (MPPTs) that are employed in photovoltaic systems (PVSs) that function under both uniform and partial shade situations are structurally summarized in this work. Well-written descriptions of the features of photovoltaic modules are followed by a variety of effective control strategies, including both AI-based and traditional controllers. In addition, appropriate knowledge of the various controllers is essential when the PV system is exposed to partial shade, keeping in mind the different control systems' classifications in this situation. A thorough analysis of several soft computing-based techniques is also included, as well as many classical controller-based PV systems. First, well-developed traditional MPPT methods are used, followed by artificial intelligence-based MPPT approaches. Later, a thorough comparison of the various MPPT-controlling approaches is established. For PV systems operating under partial shade conditions (PSCs), the advantages and disadvantages of the various MPPT techniques are outlined, contrasted, and assessed. Future research directions for MPPT are also being investigated. A collection of several datasets pertaining to various control processes that were gleaned from various research articles has also been presented. Researchers working on PV-based MPPT and those working in the sectors of renewable energy production and environmentally sustainable development would be very interested in the findings of this review study. [ABSTRACT FROM AUTHOR]

In a grid-connected photovoltaic system, the quality of energy injected by the photovoltaic system into the grid is directly linked to the topology of the inverter used and to the efficiency of its control technique. This paper addresses this problem for a two-level grid-connected photovoltaic inverter operating under low irradiance conditions. The aim is to reduce the harmonic distortion on the electrical network and therefore improve its power quality. To achieve this goal, a control strategy was set up considering the nonlinearity of the dynamic system, and the high dimension of the system model. Thus, a nonlinear controller designed using the backstepping technique is proposed. The effectiveness of this control strategy was evaluated by simulation in MATLAB/Simulink. Results show that the proposed control technique significantly improves the power quality of the grid-connected photovoltaic system by minimizing the current harmonic distortion rates in low irradiance conditions. The current harmonic distortion rates obtained for solar irradiance of 1000 W/m2, 750 W/m2, 500 W/m2, and 250 W/m2 are 0.48%, 0.78%, 1.22%, and 2.16%, respectively. The power factor is 0.988, and the DC bus voltage is maintained at its reference voltage of 600 V with a very low response time during the transient phases. A comparison of our simulation results with those found in the literature on other control techniques such as proportional-integral-derivative (PID) and synergetic controls shows the efficiency, superiority, and satisfactory performance of the proposed control scheme to minimize harmonic distortion under low irradiance conditions. The robustness and better dynamic performance of the proposed backstepping controller under varying irradiance conditions have also been shown. [ABSTRACT FROM AUTHOR]

In this research, a solar photovoltaic system with maximum power point tracking (MPPT) and battery storage is integrated into a grid-connected system using an improved three-level neutral-point-clamped (NPC) inverter. An NPC inverter with adjustable neutral-point clamping may achieve this result. To achieve this result, a modernized NPC inverter is used. Using the three-level vector modulation approach, the correct AC voltage may be generated when DC voltage conditions are present in an unbalanced situation involving an NPC inverter. A higher degree of precision is made possible by this. In-depth information on the many possible NPC inverter designs and modulation strategies was provided. By incorporating the necessary sophisticated algorithms into the NPC inverter, the necessary solar PV-MPPT functionality is made available, allowing for the regulation of power transfer among the solar PV system, the battery, and the grid. Modified INC method is proposed which has a tracking efficiency of 99.5% for varying irradiance. The use of sufficiently sophisticated algorithms makes this a reality. Using simulation with MATLAB/Simulink, we were able to examine an NPC inverter's performance in several setups. Several amounts of solar irradiation were used to test the battery's charging and discharging capabilities. The probe turned out to be fruitful. Laboratory testing ensures that the proposed method works by simulating real-world conditions. [ABSTRACT FROM AUTHOR]

A direct power control (DPC) approach is proposed in this study for a grid-tied photovoltaic (PV) voltage source inverter (VSI) to regulate active and reactive power flow directly in between utility grid and microgrid (MG) by controlling point of common coupling (PCC) voltage. The proposed PCC voltage modulated (PVM) theory-based DPC method (PVMT-DPC) is composed of nonlinear PVM, nonlinear damping, conventional feedforward, and feedback PI controllers. For grid synchronization rather than employing phase-locked-loop (PLL) technology, in this study, direct power calculation of the PCC voltage and current is adopted. Subsequently, at PCC, the computed real and reactive powers are compared with reference powers in order to generate the VSI's control signals using sinusoidal pulse width modulation (SPWM). Because of the absence of the PLL and DPC method adoption, the suggested controller has a faster convergence rate compared to traditional VSI's power controllers. Additionally, it displays nearly zero steady-state power oscillations, which assure that MG's power quality is improved significantly. To validate the proposed PVMT-DPC method's performance, real-time simulations are conducted via real-time digital simulator (RTDS) for a variety of cases. The obtained results demonstrate that using the proposed PVMT-DPC approach, PV VSI can track the reference power within 0.055 s where the output power has low steady-state oscillations and output current has lower total harmonic distortion (THD) of 1.68%. [ABSTRACT FROM AUTHOR]

This study presents the boost converter-based cascaded H-bridge (CHB) multilevel inverter with improved reliability for solar PV (photovoltaic) applications. The solar PV is associated with the boost converter to enhance DC link voltage by using the maximum power point tracking-perturb and observe (MPPT-P & O) technique. The proposed configuration is aimed toward the performance analysis of the boost converter-based CHB MLI by reducing the number of components, low total harmonic distortion (THD), reduced power, less cost function, low total standing voltage (TSV), improved reliability, and switching losses for solar PV application. In this study, a CHB multilevel inverter is used to obtain stepped pure sinusoidal AC from the solar PV array. The proposed boost converter extracts maximum power and enhances higher DC link voltage which provides high efficiency. The boost converter is integrated with a 27-level CHB multilevel inverter to generate near-sinusoidal output voltage with lower THD. The inverter is tested with linear and nonlinear loads for robustness, and during dynamic loads, inverter is stable and well suited to grid-connected applications. A detailed comparison is presented on the component count and reliability aspects with existing MLIs and 27-level MLIs. The simulation outcomes of the implemented arrangement are presented with the help of MATLAB/Simulink, an experimental prototype is developed using a dSPACE RTI1104 controller and also tested in the research laboratory for checking the possibility of the implemented arrangement. [ABSTRACT FROM AUTHOR]

Advanced power converters are being developed due to the latest developments in power electronics switches. The matrix converter (MC) assessment is the product of this drastic growth. MC is a bidirectional power flow device with a single-step energy conversion mechanism that operates at variable voltage and frequency. The main drawback of MC is the presence of harmonics due to power electronic device switching. A lot of research has been done to decrease the harmonics content present in the MC, but it is restricted to a certain level only. To overcome this limit, the harmonics are minimized in the MC by incorporating soft computing controllers. This article presents particle swarm optimization (PSO), modified PSO (MPSO), and modified hybrid PSO (MHPSO) based controllers for different loads. The proposed MC with a soft computing controller reduces the harmonics by selecting suitable switching pulses for every sample. The simulations are made using the MATLAB/Simulink environment. The results of the proposed MHPSO controller reduce the THD value from 8.654 with a PSO approach to 7.536 in the presence of nonlinear loads. [ABSTRACT FROM AUTHOR]

The goal of this article is to use MPPTs (maximum power point trackers) to extort maximum power from best configuration or combine renewable resources and energy storage systems that all work together in off-grid for electric vehicle charging. The grey wolf algorithm (GWO) searches the MPP at partial shading condition (PSC) with following two consideration one is high oscillations around GMPPs, and other is that they are unable to track the new GMPPs after it has changed positions because the seeking agents will be busy around the previous GMPPs captured. Hence, in this paper, the proposed research objective is to find solutions to these two difficulties. The issue of oscillations around GMPPs was handled by combining GWO with ANFISs (adaptive Neuro-Fuzzy inference system) to gently tune output produced power at GMPPs. ANFISs are distinguished by their near-zero oscillations and precise GMPPs capturing. The second issue called they are unable to track the new GMPPs after it has changed positions is addressed in this work by using novel initialization by GWOs (Grey wolf Optimizations). In the MATLAB-Simulink and experiments demonstrate the effectiveness of the suggested GWO-ANFIS MPPTs based off-grid station for EVs (Electrical Vehicle) battery charging. [ABSTRACT FROM AUTHOR]

This research investigated the performance of a 5 MW PV grid-connected plant in Al Fashir City, Sudan. The research aims to improve the performance and increase the efficiency of the Al Fashir plant by identifying the maximum power point and increasing the tracking efficiency based on the algorithms developed. The PV systems benefit from MPPT approaches because they improve power output and energy delivery to the load while also extending the useful life of the PV system. The P&O algorithm performance is compared to the ANN trained by the PSO method by a set of solar radiation values. However, time response, oscillation, and stability are the three most important factors to consider when evaluating the effectiveness of any MPPT algorithm. The results show that the ANN trained by the performance of the PSO algorithm was better in time response, tracking speed, and oscillation than the P&O algorithm and could identify the new power point quickly. The results of this study will assist in resizing the PV plant and improve the operation performance and efficiency to provide affordable and reliable power accessible to the people in Al Fashir city. [ABSTRACT FROM AUTHOR]

In recent years, with the rapid economic development, the development speed of all walks of life has entered a new level, and the power industry has also developed rapidly. Driven by market demand, China's power transmission range and power transmission capacity will enter a new level. At the same time, the problems brought about by the development of the power system are equally severe. Due to the large load density in individual areas, the detection of short-circuit current must be improved as an important issue. The purpose of this paper is to study how to improve the practical model of short-circuit current calculation of photovoltaic power plants, so that it can be well applied to the current high-density current detection in China. Therefore, this paper improves the recursive least squares (RLS) algorithm and applies it to the practical model of short-circuit current calculation of photovoltaic power plants and describes the improvement process of the algorithm in detail. At the same time, this paper designs relevant experiments and analysis to count the data of the improved RLS algorithm in the short-circuit current calculation of the actual photovoltaic power station and combines the data of this part to test and analyze the ability of the algorithm. The experimental results in this paper show that the improved RLS algorithm has a very good improvement in the calculation accuracy of the short-circuit current calculation of photovoltaic power plants in the actual model calculation. At the same time, the calculation efficiency is also improved, and the current tracking effect is also improved by 7%. [ABSTRACT FROM AUTHOR]

Maximum Power Point Tracking (MPPT) for photovoltaic systems has widely been studied. However, studying the impact of partial shading (due to buildings, trees, clouds, adjacent arrays, and so on) on the MPPT and achieving the global maximum is still a challenging topic. This is because not only there is a global maximum power point (GMPP) but also there are several local maximums due to the non-linear nature of the power-voltage curve after partial shading. Therefore, the conventional MPPT methods fail to track the GMPP and are commonly trapped at one of the local maximum power points. This study utilizes the Hyper-Spherical Search (HSS) algorithm in MATLAB to achieve the GMPP while improving the efficiency, convergence speed, dynamic response, and reducing the losses. To track the GMPP using the HSS algorithm, the output power for the array (PPV) is defined as the objective function, and the duty cycle of the DC-DC converter is selected as the particles' position (control variable). The performance of the proposed algorithm has been studied in three different partial shading patterns, and the simulation results confirm the capability of the algorithm in the rapid tracking of GMPP points. In addition, if the GMPP position changes over time, it will track the new GMPP with minimal oscillations. The proposed method along with PSO, P&O, ABC, and Dragon algorithms has been applied for various scenarios, and the obtained results using HSS have been compared with the four mentioned algorithms, which confirmed the effectiveness of the proposed method. Briefly, the advantages of the HSS algorithm in finding GMPP can be stated as simple implementation with few parameters, strong exploration, and exploitation during the tracking process, fast-tracking and low fluctuations during tracking, low oscillation at steady-state, high dynamic efficiency, and non-convergence to LMPP points. [ABSTRACT FROM AUTHOR]

The performance of photovoltaic (PV) systems must be predicted through accurate simulation designs before proceeding to a real-time application to avoid errors. However, predicting the cohesive relationship between current and voltage and estimating the parameters of a single diode model become a perplexing task due to insufficient data in the datasheet of PV panels. This research work presents single-diode solar PV system simulation analysis under different conditions, and the performance is improved by introducing an optimization-based maximum power point tracking (MPPT) strategy. Before simulation, a mathematical model for a single diode and optimization approaches are presented in this research work. Particle swarm optimization (PSO), genetic algorithm (GA), BAT optimization, and grey wolf optimization (GWO) model-based MPPT circuits are designed, and the performances are comparatively analyzed. The simulation results identify the nonlinear relationship between current and voltage and between power and voltage as characteristic curves for different temperature and irradiance values. For maximum power (Pmax), the maximum peak point tracking power and efficiency are analyzed to verify the optimization-based MPPT system. The simulation results demonstrate that the GWO model obtains a maximum tracking efficiency (TE) of 98%, which is much better than that of other optimization techniques. [ABSTRACT FROM AUTHOR]

In this paper, a new interleaved bidirectional buck-boost DC-DC converter is proposed. The input current of this converter is continuous and has a low ripple, that cause reduction in the size of the input filter of the converter. Because of these features, this converter is appropriate for renewable applications such as fuel cells and photovoltaic (PV) panels for obtaining maximum power in which the continuity of the input current is essential. The operation principle of this converter is detailed, and its power losses calculation shows the positive effects of the low input current ripple on its efficiency. The input current ripple of the proposed converter and conventional interleaved buck-boost converter has been calculated in detail. In addition, the comparison results of this converter with conventional interleaved buck-boost converters and other similar structures confirm that the proposed converter without utilizing extra components achieves continuous input current with low ripple. Compared with other buck-boost structures, the low input current ripple in the presented converter causes an improvement in its efficiency. An experimental prototype is implemented in the laboratory to confirm the correctness of theoretical analyses. [ABSTRACT FROM AUTHOR]

With more and more extensive research and application of wearable devices, their continuous working time has become a prominent problem which is increasingly concerned. Within the limitations of existing battery technology, environmental energy harvesting can be used to enhance the continuous working time of wearable devices. To solve this problem, this paper designs a collection system for heat energy and radiofrequency (RF) energy in the environment. This system designs a thermoelectric collector based on thermoelectric generation, an RF energy collector based on a rectifier antenna, and a mixed energy collection controller based on power trajectory tracking. This system can generate power according to the temperature difference between environment and human body and RF energy in the environment. This system uses the heart rate sampling algorithm to accurately collect the required voltage and current information while saving system energy consumption. The maximum power output algorithm based on power trajectory tracking keeps the maximum power output of the energy collection system at all times. In this paper, two kinds of environmental energy models and a mixed energy acquisition system model are established by MATLAB. After setting reasonable environmental conditions, we get the results to verify the rationality and effectiveness of this environment energy collection system. [ABSTRACT FROM AUTHOR]

Current interharmonics caused by gird‐connected PV systems have been noticed. From previous research, there is a trade‐off between the interharmonic emission and tracking performance. In cyber‐physical co‐regulation systems, there also exists a trade‐off between the cyber resource consumption and system performance. Motivated by this coincidence, a cyber‐physical co‐regulation based P&O MPPT algorithm is proposed for a three‐phase single‐stage grid‐connected PV system to mitigate the interharmonic emission in this paper. In this algorithm, a cyber‐physical model is built in which the sampling frequency is seen as the cyber state, and the step size is considered as the physical state. Based on the model, cyber and physical control laws are proposed in which the cyber and physical states are used to regulate each other. To apply the control laws, guidelines for designing control coefficients are also proposed based on the limits on the cyber and physical states to avoid chaotic behaviors caused by P&O MPPT characteristics. Compared with another mitigation algorithm without considering the cyber‐physical characteristics, the proposed algorithm can reduce the peak amplitude of the interharmonics by about 50% with a 1.35% cyber resource utilization savings and a 0.35% power efficiency improvement. [ABSTRACT FROM AUTHOR]

The photovoltaic(PV) system's efficiency can be improved with the aid of effective solar PV cell modeling. However, flawed solar cell parameters affect PV cell modeling incorrectly. The manufacturers are usually not providing all the necessary data for the exact modeling of PV cells. It is therefore necessary to efficiently predict the parameters of the PV cell. The literature discusses various optimization algorithms, but the suboptimal outcomes are obtained by most of the algorithms due to their convergence toward local minima. This paper introduces a new stochastic optimization algorithm for the estimation of solar PV cell parameters. Therefore, for the evaluation of the solar cell, a new novel chaotic algorithm is introduced in this paper called the chaotic tunicate swarm algorithm (CTSA). The proposed algorithm has a new function called an outstanding mathematical model of adaptive weights to stimulate negative and positive inputs from the spreading wave in order to find the best way to connect food with an excellent exploitation tendency and exploratory ability. For the double‐diode model, the computation time of the chaotic variants (CTSA1‐1.1885, CTSA2‐1.2502, CTSA3‐1.2962, CTSA4‐1.1204, and CTSA5‐1.2214) is better than the rest of the compared algorithms (particle swarm optimization [PSO]‐17.4532, tunicate swarm algorithm (TSA)‐2.5278, Harris hawks optimization [HHO]‐10.8942, ant lion optimizer [ALO]‐15.0214, and atom search optimization [ASO]‐9.5214). For the triple‐diode model, the computation time of the chaotic variants (CTSA1‐1.2658, CTSA2‐1.3520, CTSA3‐1.3056, CTSA4‐1.2290, and CTSA5‐1.3859) is better than the rest of the compared algorithms (PSO‐18.5421, TSA‐3.2568, HHO‐9.8754, ALO‐13.5841, and ASO‐11.8412). The superiority of proposed algorithm is established using ranking test, statistical error analysis, and sensitivity temperature variation. [ABSTRACT FROM AUTHOR]

Complexity and sensitivity related to modern machinery navigate electrical engineers more apprehensive owing to upraise power quality. In this effort, a series‐connected voltage regulating arrangement furnishes apposite aids towards this sizeable interconnected system. Consequently, a dynamic voltage restorer (DVR) is realized to proffer customized power to the end‐users. In accordance, the present research illustrates a student psychology‐based optimization modulated DVR control mechanism. In the context of real‐time realization, artificial neural network (ANN) is also embodied herein to obtain optimized online results. To intensify the potential of the implemented DVR, combined ANN and closed‐loop type 2 fuzzy logic (CLT2‐FL) modified maximum power point tracking‐based partially shaded photovoltaic (PV) aided energy storage unit is also realized in the test network topology. This hybrid CLT2‐FL module is adopted herein to trace the optimal power effectively under distinct practical scenarios. In order to assist the PV array, a supercapacitor‐based charge controller is also incorporated. Consequently, the results are evaluated to divulge the potency of the propounded mechanism against the oddity seen in the voltage waveform, thereby, exhibiting better voltage regulation and lesser harmonics with effectual optimal power tracking. [ABSTRACT FROM AUTHOR]

This paper discusses and analyses the work done in developing a Nature‐inspired optimization algorithm in a solar PV system for tracking the global maximum power point (GMPP) in partial shaded condition (PSC). Partial shading is a situation where PV panels connected in series do not receive the same solar radiation, thus exhibiting different I‐V characteristics for the individual panel. Under PSC, solar PV system output exhibits multiple local maximum power point (MPP) and a unique global MPP on the Power‐Voltage curve. Conventional maximum power point tracking (MPPT) techniques such as Perturb and Observe (P&O), incremental conductance (IC), and Hill Climbing (HC) method can only track MPP under uniform insolation conditions. It may fail to track GMPP in case of PSC and get trapped in local MPP, thereby causing loss of power that could have been tapped if the operation would have been at GMPP. To overcome the problem posed by PSC, researchers are applying the nature‐inspired optimization algorithm for tracking GMPP under partial shading conditions with fairly good results. Nature‐inspired optimization algorithm offers the advantage of solving multivariable nonlinear objective functions with constraints by exploiting the search space and can converge quickly to GMPP. Some of the most recent and famous nature‐inspired algorithms have been discussed and compared here. Simulation and hardware results of some of them are also taken in order to compare them effectively. Simulation results show that the Most Valuable Player Algorithm (MVPA) takes the least time to track the MPP in all the cases, and the MPP tracked is also comparable to the maximum while PSO with differentially perturbed velocity (PSO_DV) takes the maximum time to track the MPP in all cases. [ABSTRACT FROM AUTHOR]

Array reconfiguration techniques applied for partially shaded photovoltaic array yield maximum power output via row current minimization and shade dispersion. Both static and dynamic reconfiguration techniques are utilized for power maximization. Noticeable advantages like one time rearrangement, effective shade dispersion, and easy steps made physical or static more popular. With profound necessity to simplify the mathematical procedure and reduced complexity, in this work, a highly competent Column shift Right‐Left panel arrangement based array reconfiguration technique is proposed. It follows simple relocation steps to disperse even complex shade occurrences. To justify the versatility of the method, three different shade cases together with economy analysis and qualitative comparative study with five different existing methods including Total Cross Tied, Su Do Ku, Column method, Dominance Square, Improved Su Do Ku and Sky Scrapper methods are analysed. As a result of its implementation, power generation has aroused to a maximum of 13.47%, 4.35%, 14.01%, 9.97%, 3.45%, and 2.43%, for Top Left Corner shade case compared to conventional techniques. Further, economy analysis indicates that a maximum revenue is generated with proposed work. To strengthen the performance analysis, an experimental study on 3 × 3 PV array based on six performance metrics is carried out. For all the test cases conducted, an effective shade dispersion with the proposed method is achieved with the highest power output. [ABSTRACT FROM AUTHOR]

Summary: Beyond meeting power demand, switching to solar energy especially solar photovoltaic (PV) offers many advantages like modularity, minimal maintenance, pollution free, and zero noise. Yet, its cell modeling is critical in design, simulation analysis, evaluation, and control of solar PV system; most importantly to tap its maximum potential. However, precise PV cell modeling is complicated by PV nonlinearity, presence of large unknown model parameter, and absence of a unique method. Since number of model parameters involved is directly related to model accuracy, and efficiency; determination of its values assume high priority. Besides, application of meta‐heuristic algorithms via numerical extraction is popular as it suits for any PV cell/module types and operating conditions. However, existence of many algorithms have drawn attention toward assessment of each method based on its merits, demerits, suitability/ability to parameter estimation problem, and complexity involved. Hence, few authors reviewed the subject of PV model parameter estimation. But existing reviews focused on comparative analysis of analytical and meta‐heuristic approaches, analysis of models, and application of meta‐heuristic methods for model parameter extraction. Thus, lack a comprehensive analysis on methods based on different objective function, assessment on environmental conditions, and cumulative analysis on selective set of algorithm based on efficiency. Therefore, this work reviews optimization algorithms presented for parameter estimation focusing on (a) objective function used, (b) modeling type, (c) algorithm employed for parameter extraction, and (d) PV technology. Further, provides a comprehensive assessment on various modules types used for validation, comparisons made with methods, advantages and disadvantages associated with each method with respect to parameter estimation platform, critical analysis on each method at STC, and varying irradiance conditions. In addition, a critical evaluation on specific set of algorithm based on objective function values is also carried out. Thus explores and display the characteristics of various techniques related to PV cell modeling and serve to be a single reference for researchers working in the field of PV parameter estimation. [ABSTRACT FROM AUTHOR]

Summary: A variable step size Fuzzy logic based MPPT algorithm is proposed to ensure maximum power extraction from 1.26 kW Proton Exchange Membrane Fuel Cell (PEMFC). The Resonant PWM High Step up Converter (RPHC) is designed with soft switching capability to boost PEMFC output voltage and ensured optimum power tracking during dynamic operating condition by triggering RPHC switches with pulses generated from MPPT controller. The proposed variable step size FLC controller results are compared with conventional P&O and IC algorithm. To run a three‐phase induction motor, three‐phase Voltage source inverter connected at the output port of step up converter whose switching pattern is given by Multicarrier Sinusoidal Pulse Width Modulation (MSPWM) controller which reduces THD in output voltage and current. A detailed simulation analysis is done with MATLAB/Simulink environment and discussed the results. The hardware prototype model is implemented to validate the simulation results. [ABSTRACT FROM AUTHOR]

Summary: Traditional MPPT algorithms have demonstrated effective performance relative to their flexibility and simplicity of implementation. However, its main disadvantages are the ineffectiveness and the large oscillations around the MPP under non‐uniform solar irradiance. To achieve better performance in the power extraction from the PV system, we propose in this work a new hybrid controller focused on the bond graph and fuzzy logic (BG‐FL‐MPPT) to track the maximum power point under different weather conditions. The aim of the research is BG‐FL‐MPPT development, which will guarantee the optimum power reference operation of the system with greater efficiency, less error in the stability and voltage fluctuations. A rigorous comparison was made between the developed controller and other two MPPT algorithms, including perturbation and observation (P&O) and particle swarm optimization (PSO), in three distinct test scenarios to check the effectiveness of the suggested control. In terms of stability and robustness, it was found from the results obtained that the established controller assures the required operation of the studied system by tracking efficiency of up to 99.95% to achieve the maximum power point. A 90% faster convergence rate is obtained with a decrease in oscillations of 94.95%. The experimental tests were performed using a high‐performance experimental platform, and in the same metrological conditions, an in‐depth comparison of the experimental results with the results obtained by simulation was made. [ABSTRACT FROM AUTHOR]

In recent years, the development of renewable energy sources (RESs) and their integration with the conventional power network have increased significantly. Due to the power grid transformation brought about by the large penetration of power electronics converter‐based RESs such as wind and solar photovoltaic (PV), the operation and control of the interconnected power system has become a challenging task with respect to sustaining its stability and reliability. Power systems are confronted by several new stability issues because the dynamic behavior of converter‐interfaced renewable sources differs from conventional generation. In this respect, static synchronous compensator (STATCOM), a shunt connected flexible AC transmission system (FACTS), is recognized as a fundamental solution for maintaining power system stability. This paper presents a thorough and state‐of‐the‐art review of STATCOM control in wind‐ and/or PV‐interfaced power systems for enhancing system performance by addressing key stability issues related to rotor angle stability, voltage stability, and resonance stability. A comprehensive analysis of various control techniques of STATCOM based on conventional, adaptive, nonlinear, predictive, robust, and coordinated control and soft computing techniques is provided. Furthermore, the function of the grid‐side converter of the wind/PV plant as a STATCOM is also evaluated. Finally, the shortcomings of existing research are highlighted, current control challenges are presented, and several topics for future research are suggested. This paper provides researchers the opportunity to consider the current state of research and develop new control schemes for STATCOM to further improve the stability of modern power grids. [ABSTRACT FROM AUTHOR]

This manuscript proposes a novel centralized energy management approach (CEMA) for power quality (PQ) improvement in a solar‐battery based hybrid microgrid systems (HMSs) during both grid following and grid forming mode of operation. In the proposed HMS, a novel maximum power tracking algorithm based distributed generator control (DGC) is suggested to extract optimum power from the solar‐battery system and an energy storage control (ESC) is suggested to enhance the power transfer capability during power deficit/shortage conditions. Further, a voltage and frequency controller (VFC) is proposed to offer better coordination between the ac‐grid and dc‐grid, and improved the power quality of HMS. Moreover, the proposed CEMA smoothen the power and voltage flow of the inverter flexibly and HMS during uneven power generation, fault conditions, and consumer load demand. Even during the transition between two operating modes, CEMA also offers a stable voltage and frequency regulation for both ac and dc load. The proposed approach facilitates extra load integration without using an extra converter, degrading the power quality and cost. To test the performance of CEMA, the MATLAB environment‐based design HMS, and control model is tested during different operating conditions. [ABSTRACT FROM AUTHOR]

Background: Tracking the maximum power point (MPPT) of photovoltaic (PV) systems is essential to increase the utilization efficiency. One of the most widely used algorithms is perturb and observe (P&O) technique. Methods: In this paper, tuning algorithms based on genetic algorithm (GA) and cuckoo search (CS) are proposed to provide optimal controller parameters for P&O MPPT. This optimal tuning is crucial in P&O MPPT applications of PV systems where it is difficult to tune the controllers using conventional tuning techniques to attain good performance because of the wide variations in the system parameters and its nonlinearity. The proposed tuning algorithms are used to overcome the drawbacks of the classical P&O MPPT under rapidly changing atmospheric conditions such as oscillation around the maximum power point (MPP) and low convergence speed. Results: The robustness of the algorithms is confirmed against fast varying insolation proving its ability to track the MPP in case of random and fast changing atmospheric conditions. An experimental set up of a 1 kW PV system is carried out and implemented using dSPACE DS1103 controller board and E4360 Keysight modular solar array emulator to validate the performance of the proposed optimal tuning algorithms. The measured results are in a close agreement with the simulation and the analytical system. Conclusion: Experimental and simulation results demonstrate a superior improvement in the transient and steady‐state performances and in the maximum power tracking efficiency. The steady‐state and the transient efficiencies of the presented work are 99.95% and 94.02% which are almost 17.59% and 10.61%, respectively superior to the classical P&O one and are 14.66% and 1.52%, respectively as compared to the manual tuning approach. This proposed optimal tuning approaches can be used to enhance the performance of any other controllers. [ABSTRACT FROM AUTHOR]

Summary: The performance of the Photovoltaic (PV) system is highly affected by fluctuating climatic conditions. Due to these changing climatic conditions, the irradiance diminishes, and it results in the non‐linearity in voltage‐power (P‐V) curves of the PV system. Therefore, it is one of the reasons for the occurrence of the multiple peaks on P‐V curves instead of a single peak. Therefore, it is challenging to track the global maximum power point tracking (MPPT) under these circumstances with traditional MPPT techniques viz. perturb and observe (P&O) and fuzzy logic control (FLC). Concerning global MPP tracking, this paper proposes a novel MPPT method based on a Rao‐1 optimization algorithm. The proposed algorithm is used to overcome the drawbacks of the classical P&O, FLC, and PSO based MPPT techniques under partical shading conditions (PSCs) and rapidly changing atmospheric conditions viz. slow convergence speed and oscillation around the MPP. The proposed MPPT tracks the global MPP under any abnormal conditions like PSCs. To show the efficiency of the proposed MPPT a comparative assessment is performed with well‐established MPPT methods in the literature. The simulation results witnessed that the proposed MPPT is more superior in improving the PV system performance under normal as well as under PSCs. The proposed MPPT over the PSO technique decreases the tracking time by 72.7% for pattern 1, 29.8% for pattern 2, 66.7% for pattern 3, 61.9% for pattern 5, 27.8% for pattern 6, and improves the tracking efficiency in all shading patterns. [ABSTRACT FROM AUTHOR]

Summary: This work presents a new Maximum Power Point Tracking (MPPT) scheme which predicts the local peak positions precisely and tracks the global peak under partial shading effectively. In addition to that, a skipping mechanism is integrated into it, which helps the MPPT to avoid scanning several sections of the I‐V or P‐V curve. Consequently, the global peak tracking gets accurate and faster than existing MPPT techniques. Several rigorous experiments are carried out in Matlab/Simulink to verify the behaviour of the MPPT. It is observed that under deep shading where the global peak resides on the left zone in voltage profile, tracking speed gets significantly faster. Furthermore, the proposed scheme is implemented in hardware through buck‐boost converter in conjunction with dSpace DS1104 board to justify the applicability. Tracking results under several partial shading shows that the proposed method outperforms other MPPT techniques namely Modified Incremental Conductance (MIC), Ant colony optimization‐P&O (ACO‐P&O) and Cuckoo Search (CS) by a significant margin. Tracking speed is improved by 2 to 3 times depending on the shading pattern and efficiency is well ensured over 99% under all cases. [ABSTRACT FROM AUTHOR]

Summary: Enhancing distribution system operation accomplished with the integration of renewable energy resources (RERs) has several technical, economical, and environmental dimensions. In this regard, this paper presents an optimal integration procedure of Distributed Generation (DG) based on Photovoltaic panel (PV) and Distribution Static Compensator (DSTATCOM) in Electrical Distribution System (EDS). The proposed procedure is formulated as a multi‐objective function (MOF). The considered objectives that reflect the technical, economic, and environmental issues, are Active Power Loss Level (APLL), Short Circuit Level (SCL), Voltage Deviation Level (VDL), Net Saving Level (NSL), and Environmental Pollution Reduction Level (EPRL). The proposed procedure investigates several hybrid optimization methods that combine the firefly algorithm (FA) with various acceleration coefficients PSO algorithms to improve the overall solution quality of the hybrid algorithms compared with the individual algorithms. To prove the capability of the proposed procedure, four different cases are tested on IEEE 33‐bus and 69‐bus EDSs. Added to that, the proposed algorithms are extended to practical Algerian EDS in Adrar City 205‐bus. Results obtained by the hybrid FA‐SCAC‐PSO algorithm showed that the simultaneous allocation of multiple DG and DSTATCOM in all standard and practical test systems significantly reduces the loss and enhances the voltage profile. An energy‐efficient analysis to proceed for different cases studied based on the best hybrid FA‐SCAC‐PSO algorithm to reach the best value of MOF compared to other algorithms, moreover the capability to achieve the optimal allocation of DG and DSTATCOM by maintaining the voltages profile within the permissible limit, whatever the variation of load. Significant technical economic and environmental achievements are found for different case studies especially in the existence of DGs and DSTATCOM devices. [ABSTRACT FROM AUTHOR]

Summary Partial shading conditions generate multiple peaks in the P‐V curve of photovoltaic (PV) arrays. Smart MPPT optimization techniques should be used to capture the global peak (GP) and avoid being trapped in one of the local peaks (LPs). The tracking of the GP should be fast and reliable to enhance the stability and increase the generated efficiency of the PV systems. Bat algorithm (BA) is one of the fastest swarm optimization techniques. The BA control parameters (BA‐CPs) have substantial effects on their performance. This paper introduced a nested BA strategy called BA‐BA strategy to determine the optimal values of control parameters of BA for the lowest convergence time and failure convergence rate to be used in the online MPPT of PV systems. The inner BA loop used the BA as an MPPT of the PV system, meanwhile, the outer BA loop used the inner BA loop as a fitness function to determine the optimal BA‐CPs for minimum convergence time and failure rate. Ten benchmark BA strategies, particle swarm optimization (PSO), and cuckoo search (CS) algorithm have been used to compare their results with the results obtained from the BA‐BA strategy. The results of the BA‐BA strategy reduced the convergence time of 250% of the time associated with the best benchmark BA strategy, 518%, and 395% as compared to the PSO, and CS algorithm, respectively. The simulation and experimental results obtained from the BA‐BA strategy showed its superior for determining the optimal control parameters for BA in MPPT of PV systems or any other applications. [ABSTRACT FROM AUTHOR]

Summary: This paper introduces a novel genetic optimize multi‐control adaptive fractional order PID (AFOPID) for Photovoltaic (PV) and Wind connected grid system. The proposed AFOPID controller is optimized by a genetic algorithm (GA) to initialize the controller parameters. The renewable energy sources are mathematically modeled using multi control approach (MCA). In the proposed work, the MCA involves the maximum power point tracking (MPPT), dc link voltage, and current control and quadrature axis modeling. Furthermore, the current control functionalities are performed through an adaptive approach of AFOPID, where the controlling parameters are updated by measured error at every instant. The idea behind the research is to improve the tracking efficiency by introducing better control in order to gain maximum power from the source with minimized total harmonic distortion (THD). The proposed control scheme is tested using computer‐aided experimentation by varying the output of renewable energy sources, inverter uncertainty, and grid voltage variations. The results are benchmarked against the conventional fuzzy logic controllers, fractional‐order PID, and PI controllers. Moreover, to evaluate the effectiveness of the proposed controller, the MCA‐AFOPID is compared with ant colony optimization (ACO) and particle swarm optimization (PSO) optimized FOPID controller respectively. The proposed controller outperforms as compared to other controller. [ABSTRACT FROM AUTHOR]

Summary: In this article, particle swarm optimized proportional integral (PI) controlled DC‐DC buck converter‐based proton‐exchange membrane fuel cell emulator has been proposed to test the maximum power point tracking algorithm and battery charging controller. Particle swarm optimization is used to optimize the proportional gain (Kp) and integral gain (Ki) of the proportional integral controller for emulating the characteristics of the PEM fuel cell. The simulation model of the proposed PEM fuel cell emulator is created and tested using MATLAB Simulink package. To validate the effectiveness of the proposed PEM fuel cell emulator, it is tested under different operating conditions. The polarization characteristics of the PEM fuel cell emulator are compared with PEM fuel cell reference model. The suitability of the PEM fuel cell emulator has been tested with MPPT algorithm and MPPT battery charging controller. Also, real‐time testing of the proposed PEM fuel cell emulator has been realized through experimental set up and the corresponding results are analyzed. [ABSTRACT FROM AUTHOR]

Summary: As a global common trend for fossil fuels independence, renewable energy plays a great role to save a clean source of energy. As a result of the high solar energy potential in Egypt, successive incentive polices had been introduced by the Egyptian electricity authority to encourage the deployment of small‐scale residential rooftop photovoltaic (PV) systems. This paper explores the impacts of installing a grid‐connected PV battery system from both technical and economic point of view under the existing incentive policy and energy purchasing and selling price in Egypt. The Egypt case is considered as a case study. The study investigates the current Egyptian Incentive Policy situation and criteria for high electricity load profile. The economic evaluation of various sizes of the PV battery system is carried out based on different economic measures such as net present value (NPV), self‐sufficiency (S‐S), and electricity bill savings. The methodology is based on the assessment of different technical and economical indices as well as on performing sensitivity analysis. A MATLAB code was purposely developed and implemented to evaluate the economic effect of the installed system considering the effect of battery capital cost and discount rate variations. A net energy metering (NEM) incentive policy is suggested to increase and maximize the financial profits from installing PV battery system and increase the independency from the utility grid. The results showed that doubling the sellback power price to $0.089/kWh instead of $0.04/kWh will decrease the profitable PV system size to the half and will increase the NPV to the double. Under FiT incentive policy, installing 25 kWp PV system can achieve 50% of S‐S and adding 12.5 kWh of batteries will increase it to 75%, while under the NEM incentive policy, installing 15 kWp PV system can achieve 47% of S‐S and the 75% S‐S can be achieved by adding 15 kWh of batteries. [ABSTRACT FROM AUTHOR]

Summary: In this paper, a photovoltaic (PV) array tied modified three‐port interleaved flyback converter (MTPIFC) is proposed to power shunt active power filter (SHAPF). The MTPIFC is intended to feed a SHAPF from a PV power source to overcome the power quality issues associated with the interconnection of nonlinear loads with the low‐power distribution network. The three‐phase six‐level cascaded multi‐level inverter operated as a SHAPF reduces the current harmonics and the number of active and passive components compared to widely used MLI. This study also presents a DQ current control method with a modified phase‐locked loop to generate the required reference signal for the PV‐SHAPF. Extensive recreation and test contemplates are done to confirm the capacity of the suggested PV‐SHAPF. [ABSTRACT FROM AUTHOR]

Summary: Increasing implementations of renewable energy resources to migrate from fossil fuel based electric power to clean energies have been creating new technical challenges due to their integration into an existing electrical grid. In this research, a power electronic converter based on fuzzy‐logic controller is developed to govern the transfer and control of power in a grid‐connected residential photovoltaic (PV) system with battery storage. A bidirectional dc‐dc converter is designed for power transfer between the loads and the battery. A bidirectional ac‐dc converter is used as the interface between the PV array and the electricity grid. The fuzzy‐logic controller is designed to meet the user power requirement—with the PV array and the battery sized to meet the critical load requirement on site. The results indicate that the fuzzy‐logic‐based power conversion helped the system to adjust to off‐grid, low‐battery, full‐battery, and on‐grid power conditions. The main merit of the design is simplicity in being able to manage the limited supplies from the grid and the renewable PV installation using carefully sized storage that serves critical loads within specific days of power autonomy. [ABSTRACT FROM AUTHOR]

Objective: To maintain the operation of a wind turbine at its maximum efficiency and for the extraction of maximum power from the wind. Method In this paper, at first, a novel application of fractional‐order nonlinear proportional‐integral‐derivative (FONPID) controller is proposed in the machine side converter (MSC) control loop of a 2 MW grid‐connected wind energy system. Then, the grid side converter (GSC) is controlled to ensure the unity power factor of the understudy system. To extract the maximum power from the wind, the application of the proposed controller is applied to a well‐established TSR MPPT control method, which compares optimal and actual values of rotor speed, and generated error is given to the proposed controller to vary the rotor speed accordingly. Moreover, improved MPPT performance offered by the proposed FONPID controller has also been compared to well‐established existing controllers based TSR MPPT methods. Furthermore, parameters of the proposed and existing controllers in the TSR MPPT control loop are also tuned using teaching‐learning based optimization (TLBO) and obtained performance is compared with the performance of particle swarm optimization (PSO) to show effectiveness. Results The generator speed offered by the proposed FONPID based TSR MPPT method effectively tracks its reference values far better than the extant controller based TSR MPPT method, whereas extant NPID has less overshoot as compared to the extant PID based TSR MPPT method. Conclusion To perform the effective operation of achieving MPP, q‐axis current of the stator has been controlled by the proposed FONPID based TSR MPPT method in such a style that rotor speed can be operated at its optimal value where the generator has the maximum power for given wind speed. DC‐link voltage is controlled at its rated value to guarantee the unity power factor operation using the GSC controller. FONPID based TSR MPPT method provides a better and robust MPPT operation than the PID, NPID, and FOPID controllers based TSR MPPT method. The performance has been assessed in terms of minimized fitness function value, steady‐state error, settling time, and percentage overshoot. [ABSTRACT FROM AUTHOR]

Under partial shading conditions (PSCs), the I‐V curve of PV systems consist of multiple local maximum power points (MPP's) and one global MPP which is required to extract the peak power of solar PV. In this article, an improved variable step size‐radial basis function algorithm (VSS‐RBFA) based MPPT controller is implemented to track the MPP with high speed. The advantages of proposed MPPT controller are high convergence speed, reduced oscillations across MPP, and takes less time to track MPP. Also, a universal high step‐up boost converter (HSBC) is proposed in this work to step up the PV voltage. The attractive features of HSBC are continuous input current, high voltage gain, less voltage stress on switches, and wide input and output operation. The proposed converter continuous conduction mode (CCM) and discontinuous conduction mode (DCM) of operations are compared successfully at the steady‐state operating condition. The simulation results of the proposed PV fed HSBC system is validated under uniform and PSC's of solar PV. In addition, the proposed converter results are verified experimentally by using a programmable DC source. [ABSTRACT FROM AUTHOR]

Summary: Rapid deployment of distributed generation resources such as photovoltaic systems, wind farms, and other power electronics‐based loads has emphasized the requirement for tap‐changing transformers that minimize voltage variations and phase imbalances. Thus, various power‐flow algorithms able to model such a tap‐changing transformer have been proposed. The algorithms include a method that uses the bus impedance or admittance matrix. However, particularly the previous algorithms that use the impedance matrix did not take tap‐changing transformers and P‐V buses into account. Thus, this study models tap‐changing transformers for a power‐flow algorithm using the impedance matrix. For this purpose, it proposes a unified steady‐state T shaped transformer model with a tap changer on the primary or secondary side. The proposed power‐flow calculation algorithm also models P‐V buses by the sensitivity impedance matrix. Since the proposed method reduces the inversion of matrices, it can be faster than the Newton‐Raphson and fast decoupled methods (eg, the modified IEEE 30‐bus test system added by 3000 or more nodes), not losing the accuracy. [ABSTRACT FROM AUTHOR]

Back ground and Aim: In this work, a new control scheme is developed to track the peak power from a solar energized grid‐tied three‐level diode‐clamped split source inverter (DCSSI). Material and method: Two isolated photovoltaic sources (PV) are considered as sources for the topology. The impedance network serves as a voltage booster and enhances the input PV voltage. Two individual perturb and observe maximum power tracking algorithms are used to pursue the peak power and to generate two individual dc‐link voltage references. A new dc‐link voltage reference is developed by the addition of the two individual voltage references. Results: The proposed control scheme is tested with different cases to investigate the optimum performance of the DCSSI. Primarily, the control scheme is examined with MATLAB/SIMULINK. To validate experimentally, a 5KVA DCSSI prototype is designed along with two individual impedance networks. An SP‐110 pyranometer is used to sense the variable irradiance. A Spartan‐6 XC6SLX25 field programmable logic array (FPGA) is used to generate the control algorithm for the DCSSI. Conclusion: Simulation and experimental results demonstrate the robustness of the proposed control scheme. [ABSTRACT FROM AUTHOR]

The direct and indirect control methods are commonly used for maximum power point tracker (MPPT) of photovoltaic (PV) systems. Due to the absence of the literature that assess their performance in a comprehensive way, this work attempts to analyze the effectiveness of both control methods for the perturb and observe (P&O) MPPT algorithm. The MATLAB/Simulink simulation is verified experimentally using a PV array simulator and the dSPACE DS1104 DSP board driving a buck‐boost converter. The results show that the indirect method exhibits lower steady‐state oscillation and is less sensitive to rapid irradiance change and load variations. It increases the steady‐state efficiency by 1.6%. Furthermore, under irradiance and load step changes, the transient efficiency increases by 29% and 30%, respectively. Based on these findings, it is envisaged that the indirect method is more suitable to be used as the controller in conjunction with the MPPT algorithm. [ABSTRACT FROM AUTHOR]

Summary: Background: In this paper, a new hybrid global maximum power point tracking (GMPPT) technique is proposed for faster and accurate tracking of global maximum power point (GMPP) without premature convergence. It is a combination of modified particle swarm optimization (PSO) and perturb and observe (P&O) methods. The proposed GMPPT technique, adaptive butterfly PSO (ABF‐PSO) uses butterfly swarm intelligence for modifying the conventional PSO algorithm with parameter tuning to avoid premature convergence. Aims: Hybrid global maximum power point tracking (GMPPT) technique is proposed for faster and accurate tracking of global maximum power point (GMPP) without premature convergence. Further, a new reinitialization of particles for any irradiance change is proposed to get faster tracking. Materials & Methods: In the proposed hybrid GMPPT technique, first GP region is easily identified with adaptive sensitivity parameter of the ABF‐PSO algorithm and in the region identified, GMPP tracking is continued with P&O algorithm with variable length perturbations to avoid the unnecessary exploration of search space even after reaching global peak (GP) region. Results: The combined effect of adaptive parameters, global region identification with adaptive sensitivity, proposed reinitialization method, and steady‐state tracking with variable step P&O results in fast and accurate tracking of GMPP with low power oscillations during GP region identification stage and steady‐state. Discussion: Boost DC‐DC converter is used as an MPPT controller to test the performance of the proposed algorithm under different irradiance patterns by using MATLAB/Simulink model and hardware prototype developed. Conclusion: The combined effect of adaptive parameters, global region identification with adaptive sensitivity, proposed reinitialization method, and steady‐state tracking with variable step P&O results in fast and accurate tracking of GMPP with low power oscillations during GP region identification stage and steady‐state. [ABSTRACT FROM AUTHOR]

Summary: Generally, photovoltaic (PV) panels are affected by variety of internal and external faults. Hotspot is regarded as an internal and permanent fault that is highly destructive in solar panels. In this study, a novel approach based on PV output current trajectory is proposed for hotspot detection in PV strings. The hotspot detection criterion consists of two parts. First, the Teager‐Kaiser energy operator technique is applied for current change detection. Then, a novel hotspot detection index based on the cumulative rate slope calculation of PV current is applied. The proposed index has the advantage to distinguish between hotspot condition and other faults only by utilization of current measurement. The thermal behavior and the current trajectory are evaluated during hotspot condition. It is shown that the current characteristic of the cell during hotspot condition has a unique behavior, which is also justified by mathematical analysis. Different shading scenarios are considered in this study. However, the proposed approach can easily detect the one which cause hotspot condition and distinguish it from other type of scenarios. Therefore, the proposed approach can detect hotspot fault before the solar cell destruction. MATLAB simulations are applied in order to confirm the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

Summary: This article intends to present a compendious review to extract maximum power in solar photovoltaic (PV) systems under varying environmental conditions and partial shading conditions by enumerating various circuit‐based topologies and different state‐of‐the‐art maximum power point techniques (MPPT). Partial shading reduces the overall efficiency of the PV system; therefore techniques that are dealing with partial shading play an important part in the power conditioning unit of all PV system connected to the stand‐alone mode or grid mode. Various circuit‐based topologies and various algorithms have been broadly discussed till date. As every algorithm is associated with its own merits and demerit, hence an extensive literature survey is required while planning for PV generating station under normal and partial shading condition. In this article, a comprehensive review of shading mitigation using different topologies has been done. The article on shading mitigation is broadly divided into two major groups. The first group includes all major circuit‐based topologies and the second group includes MPPT based techniques, which has been further classified into modified conventional techniques, soft computing techniques, and hybrid techniques. This comprehensive review presents an assessment of all techniques according to parameters like converter used, tracking speed, complexity, efficiency, number of sensors under partial shading condition would certainly provide a single platform to carry forward their research in solar PV application. [ABSTRACT FROM AUTHOR]

Summary: Photovoltaic (PV) energy represents one of the most important renewable energies, but its disadvantage resides in its maximum power point, which varies according to meteorological changes that make the efficiency low. Intelligent techniques, using the maximum power point tracking (MPPT) method, can achieve an efficient real‐time tracking of this point in order to ensure optimal functioning of the system. The output power of the PV system is removed from solar irradiation and cell temperature of the PV panel type SOLON 55W. Therefore, it is essential to harvest the generated power of the PV system and optimally exploit the collected solar energy. For this objective, this work treats on a new artificial neural network‐particle swarm optimization approach (ANN‐PSO). The ANN is used to predict the solar irradiation level and cell temperature followed by PSO to optimize the power generation and optimally track the solar power of the PV panel type SOLON 55W based on various operation conditions under changes in environmental conditions. The simulation results of the proposed approach give a minimum error with a relevant efficiency, that is, the power provided by ANN‐PSO approach is optimal and closer to the PV power. Consequently, this novel approach ANN‐PSO shows its major capability to extract the optimal power with excellent efficiency up of 97%. For this objective, this work treats a new hybrid ANN‐PSO approach. [ABSTRACT FROM AUTHOR]

Summary: This article proposes hierarchical power management and energy control aimed at improving the reliability and efficiency of electric power generation from a wind farm connected to the grid. The wind farm consists of three wind energy conversion systems (WECS) each consisting of a wind turbine, a double‐feed induction generator and five‐level power converters. The first control layer includes a maximum power point tracking algorithm to extract the maximum power from the wind energy source based on an optimal torque control strategy. The real and reactive power flow from the WECS to the grid is controlled with a non‐linear backstepping controller based on the Lyapunov stability theory. Finally, a DC bus voltage controller with a clamping bridge is employed to ensure the stability of the DC bus voltage and to compensate for transient disturbances caused by load fluctuations. The second layer of control ensures coordination between the wind farm, the power grid and the load to ensure reliable and efficient power supply. The model of the grid‐connected wind farm and the proposed control scheme are developed using MATLAB and Sim Power Systems Toolbox. A series of simulation scenarios are presented to evaluate the performance of the proposed control scheme under various operating conditions. [ABSTRACT FROM AUTHOR]

Summary: This paper presents a system for tracking the maximum power point (MPP) and output voltage regulation of photovoltaic cells. The system includes two stages of cascading dc/dc converters: the first one is a boost converter used for tracking the MPP using the perturb and observe algorithm. Meanwhile, a buck converter regulates the output voltage employing the active disturbance rejection control based on an extended state observer and the differential flatness property. The hardware architecture was modeled using high‐level tools of hardware abstraction and implemented in a FPGA Artix‐7 made by Xilinx. Finally, the performance of the proposed system is shown through a series of experiments that consisted of changing the irradiance and temperature conditions and changes in the system parameters. [ABSTRACT FROM AUTHOR]

Summary: This paper assesses the behavior of a wind energy conversion system (WECS) under the fuzzy control in several sites located in Morocco. The sites involved in this study are located in coastal areas, namely, Assila, Houceima, Tetouan, Dakhla, Essaouira, and Laayoun. Furthermore, the first part deals with an inventory and state of art of the wind potential, achievements, work in progress, and future projects in the Kingdom of Morocco. Subsequently, a statistical analysis of the wind data and concerning the wind speed and direction in relevant geographical areas was presented in detail. The second part of the paper examines the control of WECS which is based on the direct control of the permanent magnet synchronous generator. Generator connection to the power grid is achieved by two power converters in back‐to‐back configuration controlled by pulse width modulation. The whole system modeling including the generator modeling was discussed. The control development based on (Fuzzy‐proportional‐integral) corrector for the machine‐side converter and the maximization of the power extracted from the wind using the maximum power point tracking technique have been developed. The grid‐side converter ensures the system connection to the grid with good power quality and controls the DC bus voltage. The control strategy is verified through the simulation in the Matlab‐Simulink environment to validate and evaluate the dynamic performance of the system using real wind measurements for the selected sites. The obtained results prove the effectiveness of the intended control. Interestingly, the southern zone of Morocco is more convenient for the exploitation of electricity production compared to the northern zone of the country which it can be beneficial for autonomous applications. [ABSTRACT FROM AUTHOR]

Summary: In this paper, load frequency control of photovoltaic (PV)‐thermal‐thermal interconnected three area power system is proposed with fuzzy gain scheduling controller. Grid‐connected PV power system has quick rising annual rate and is rapidly becoming a significant part of the energy balance in the power systems. Reduction in the PV modules cost increases the application of PV. In recent days, increase in load demand necessitates the interconnected power systems. Power quality concerning frequency plays a major role in life and efficiency of the load. The fuzzy logic controller is an efficient controller to deal with the unknown data; in the LFC, the load demand is unpredictable; hence, fuzzy is applied for LFC in this analysis. Proportional integral (PI) controller plays a significant role in real‐time LFC. Therefore, in this article, fuzzy gain scheduling controller is proposed to tune gains of PI controller to improve performance of interconnected power systems. To validate the performance of proposed system, it is compared with the conventional PI controller‐based LFC. The entire system is analyzed using Matlab with various loads. [ABSTRACT FROM AUTHOR]

This paper presents a photovoltaic (PV)–grid integrated system feeding an induction motor‐driven water pumping system. The power transfer is controlled by regulating the direct current (DC) link voltage. This system is used for feeding the induction motor‐driven water pump primarily and feeding the utility if the water pumping is not required. The power flow is controlled by a power factor‐corrected Vienna rectifier. The reduction in sensors makes the system cost‐effective. In addition, a flux estimation technique is proposed, which has good DC offset removal capability. The modified space vector modulation (SVM) technique is used for even‐harmonics elimination in grid voltage. Simulated results are validated by test results obtained on a developed prototype under different environmental conditions. [ABSTRACT FROM AUTHOR]

Summary: The net‐load ramping occurs when the output power of renewable energy resources is decreased simultaneously with a rise in the load during early evening hours. Thus, in this paper, the unfavorable effects of ramping are mitigated via the multi‐microgrid system without additional investment. In the proposed model, microgrids under study include micro turbine, photovoltaic, wind turbine, phosphoric acid fuel cell, energy storage system, and demand response program. The mentioned microgrids attempt to exchange power with the upstream grid at appropriate intervals by incorporating hourly dynamic penalty costs to their operational costs so as to moderate the ramping of the distribution grid load profile. The minimization of the total cost of operation is formulated for the multi‐microgrid system. As a result, it is possible to eliminate the effects of ramping using proper management of the units and exchanged power in the proposed scheme. Also, the numerical results indicated the usefulness and applicability of the proposed model through its application on a typical distribution test system. [ABSTRACT FROM AUTHOR]

Summary: Conventional variable perturbation–size maximum power point (MPP) tracking methods use a constant multiplying factor to enable fast convergence process. However, it potentially leads to the sluggish dynamic response. In this context, a novel autoscaling variable perturbation–size MPP tracking algorithm is proposed to precisely recognize the MPP under an abrupt change in solar irradiance. Initially, a new perturbation size scaling function of the duty cycle is defined, which typically modulates the DC‐DC boost converter output. The principle objective of employing this algorithm is to enable the fast dynamic response while harvesting steady‐state power with nearly zero sustained power oscillations around the MPP. In a second step, a method is proposed to improve the decision‐making system during a sudden change in irradiance. The proposed MPP technique optimally achieves 99.72% tracking efficiency without much computational intensiveness, which is better compared with previous MPP tracking methods. The adaptability of the proposed technique is validated through a comprehensive set of MATLAB/Simulink software simulation studies followed by a low‐cost STM32F407VGT6‐based microcontroller‐based experimental setup. Furthermore, the reliability of the proposed algorithm is also investigated. The result implies that the proposed MPP tracker operates satisfactorily under sudden changes in irradiance. [ABSTRACT FROM AUTHOR]