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Changes are emerging that will significantly alter structure and operation of this century's distribution networks, and photovoltaic (PV) systems will play greater role in energy sector, with implications for power system reliability. Considering uncertainties in solar irradiance and electrical loads and incorporating them into the optimization problem within an appropriate methodology is becoming increasingly important in reshaping distribution networks. In this paper, uncertainty scenarios are handled with Monte Carlo Simulation (MCS) under genetic algorithm (GA) and differential evolution- (DE-) based optimization, and probability distribution functions (pdf) of bus voltages and line current are obtained to be used in chance-constrained stochastic programming. This present study focuses on investigating impact of uncertainties in PV system operating under different irradiance scenarios on power loss with probabilistic constraints in distribution networks instead of precise deterministic limits to contribute more efficient and reliable use of energy. By combining meta-heuristic optimization and MCS technique under one framework, this paper contributes to knowledge base of how to allocate PV plants within distribution networks under chance-constrained strategy. In order to show the effectiveness of the proposed methodology, obtained optimization results are tested using MCS under set of uncertainty conditions and network constraints are evaluated for limit violation probabilities. The effectiveness of this method is investigated based on comparative results of two different optimization methods through probabilistic analysis and simulation. [ABSTRACT FROM AUTHOR]

Accurate PV power forecasting is becoming a mandatory task to integrate the PV system into the power grid, schedule it, and ensure the safety of the power grid. In this paper, a novel model for PV power prediction using AP-LSTNet has been proposed. It consists of a combination of affinity propagation clustering and long-term and short-term time series network models. First, the affinity propagation algorithm is used to divide the regionally distributed photovoltaic station clusters into different seasons. The Pearson correlation coefficient is used to determine the strong correlation between meteorological factors of photovoltaic power, and the bilinear interpolation method is used to encrypt the meteorological data of the corresponding photovoltaic station cluster. Furthermore, LSTNet is used to mine the long-term and short-term temporal and spatial dependence of photovoltaic power, and meteorological factor series and linear components of auto-regression are superimposed to realize the simultaneous prediction of multiple photovoltaic stations in the group. Finally, PV power plants in five cities, Wuwei, Jinchang, Zhangye, Jiuquan, and Jiayuguan in the Hexi region of Gansu Province, China, will be selected to test the proposed model. The experimental comparison shows that the prediction model achieves high prediction accuracy and robustness. [ABSTRACT FROM AUTHOR]

This paper presents a grey-box model of a DC/DC boost converter for PV energy systems. The proposed model contains a white-box model part and a black-box model part together to prepare a better model for the PV boost converter. The white-box model part is used for knowledge of the circuit by mathematical equations since the black-box model part is used for unknown parameters such as temperature and electromagnetic interference. The black-box part of the proposed model is created by a nonlinear system identification of a real boost converter circuit with an artificial neural network. The precision of the mathematical model and the advantages of the fast prediction ability of the artificial neural network were used together. The proposed grey-box model is compared with the existing state-space and black-box models and experimental results. The results of the study showed that the average correlation between the proposed grey-box model output and the experimental results is 97.52%. Therefore, the proposed model can be used for analyzing DC/DC boost converter output characteristics before field applications. [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]

The global demand of electrical power has increased enormously due to various reasons such as fast-changing and challenging technologies, climatic change, economic growth, and lifestyle of mankind. Due to global warming issues and the depletion of conventional sources of power generation, the utilization of renewable energy sources has drastically increased. So, many challenges exist in integrating the microgrid with AC grid and load. The alternative arm converter (AAC) is among the most innovative converter topologies used in high voltage direct current (HVDC) applications. This research work presents a new control strategy to generate pulses to trigger the switches in the AAC in a proper sequence to obtain a smooth output waveform. The AAC output is controlled by implementing various controllers such as the proportional-integral-derivative (PID) controller, fractional order PID (FOPID) controller, and FOPID controller tuned by metaheuristic algorithm-bacterial foraging optimization technique (BFOT). Also, a comparative analysis is performed based on the spectral analysis of the output voltage obtained. In comparison to other controllers, the FOPID controller optimized by the bacterial foraging optimization technique (BFOT) produced the least total harmonic distortion (THD) of the AAC output voltage. In addition, this paper also discusses about the performance and analysis on the design of an energy management system (EMS) to optimally utilize the energy sources such as PV system, wind system, and battery based on their availability which feed the AAC. The energy management system controls the entire integrated system in association with an integrated CUK-SEPIC converter to fulfil the load demand at the point of common coupling, either from the microgrid or the AC grid. A nine-level AAC model is designed integrating the microgrid, grid, and industrial loads with an energy management system using MATLAB/Simulink. The performance parameters of the entire model are analysed at every stage to provide stabilized output to meet the load demand. [ABSTRACT FROM AUTHOR]

Researchers are paying attention to the current trend of electric vehicles (EVs), but there are not many places to charge them and serve as electric vehicle charging stations (EVCSs). In order to prevent the lack of EVCS for battery EVs (BEVs) on any road with all modes of operation, this paper proposed the design of a novel configuration and control structures for the isolated charging station (ICS) based on the solar PV system for efficient energy utilization to charge battery EVs (BEVs) with flexible double function cascaded converter (MPPT and DC-link voltage regulation). This was done with the aid of a battery energy storage system (BESS) as a backup/auxiliary source. The PV system is reliant on solar radiation and the daily load profile. Therefore, the BESS is employed to provide continuous power to BEVs and overcome PV's intermittent nature. The cascaded converter is used to achieve the MPP and to regulate the DC-link voltage to its reference value (100 V), while the buck-boost matching bidirectional DC-DC voltage converters (MBDVCs) are used for charging and discharging mode/buck and boost mode, respectively, of BEVs and BESSs. Additionally, the MBDVCs are used as an interface between the ICS sources with the load through the developed control systems. The outcomes of various operating modes show that the system functions effectively. To verify the system performance, the MATLAB/Simulink application builds the system setup. [ABSTRACT FROM AUTHOR]

Recent research has been focussed on renewable energy due to the rising need for electrical energy. Renewable energy has a low environmental impact compared to other energy sources. As a result, renewable energy sources (RESs) are the best option for generating electricity. Solar photovoltaic is one of the largest renewable power generators. Solar photovoltaic (PV) is connected to the load via power electronic converters. Most PV installations need a two-stage conversion process consisting of a boost converter to increase the load voltage and an AC-to-DC voltage source inverter to power the load. The Z-source inverter (ZSI) can confront the shortcomings of VSI and two-stage conversions. ZSI connects the PV system to the load and is used to increase the system's performance. This paper discusses the performance of various topologies of ZSI, such as traditional Z-source inverters (XZSIs); for integrating a PV source into a load, switched inductor Z-source inverters (SIZSIs) and transient Z-source inverters (TZSIs) are used. Also, artificial neural networks (ANNs), fuzzy logic controller (FLC), and adaptive neuro-fuzzy inference system (ANFIS)-based MPPT techniques are discussed for obtaining maximum power from PV panels. Based on the maximum power, the shoot-through duty ratio has been adjusted. [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]

Power quality is the main problem with the power system network. Poor electricity quality may cause disruptions and financial challenges for consumers. Additionally, it could cause electronic gadgets to overheat, be damaged, or operate inadvertently. Transformers and other components of the power distribution system may also overheat and experience core saturation. This study investigates potential problems with the quality of the electricity in a photovoltaic linked power system. This paper suggests a new optimization method for day-ahead trading and control in DC microgrid power management (MG). The goal of the multiobjective optimization dispatch (MOOD) problem is to lower overall operational costs as well as the costs associated with power loss in efficient conservation systems and exhaust emission quantities such as nitrogen oxides, sulphur dioxide, and carbon dioxide. Using the weighted sum approach, the multiobjective optimization problem is reduced to a single optimization problem. The analytical hierarchy process (AHP) method is then used to calculate the weight coefficients while accounting for each objective function's preferences. Power balancing, high levels of renewable energy penetration, the most effective scheduling of battery charging and discharging, control of load curtailment, and the technical limitations of the system are all taken into account when evaluating the system's performance in both grid-connected and standalone operation modes. The ant lion optimizer (ALO) technique is taken into account to tackle MOOD, comparing the effectiveness of the proposed method to other well-known heuristic optimization techniques. The simulation's results demonstrate how effectively the proposed strategy can address the coordinated control and optimization dispatch difficulties. They also found that operating the MG system economically in grid-connected mode can save overall costs by roughly 4.70% compared to doing it in independent mode. [ABSTRACT FROM AUTHOR]

The increasing penetration of distributed energy resources (DER) has imposed several challenges in the analysis and operation distribution networks. In the last decade, the implementation of battery energy storage systems (BESS) in electric networks has caught the interest in research since the results have shown multiple positive effects when deployed optimally. However, a complex formulation of the optimization problem regarding DER implementations can easly become nonconvex, thus limiting the scope of the results (quality) and affecting the computational efficiency. In this paper, convex formulations of the optimal power flow (OPF) problem for DER (PV and BESS) installations in San Andres distribution network were implemented to minimize power losses. Four main simulation cases were stablished covering convex power flow analysis, convex optimal power flow to locate and size dispatchable and nondispatchable DER (PV) with demand and irradiation profiles, and the inclusion of aggregated and distributed PV and BESS systems. The computational realization of those formulations was made with three different software packages: CVX in python, CPLEX, and MATLAB (MATPOWER/PSO). The results show that installing DER capacity (both PV and/or BESS) can substantially improve the power losses in distribution networks, especially if considered distributed instead of aggregated, achieving reductions up to 75% for power losses and up to 57% for conventional generation utilization. Besides power losses, it was observed that optimal DER (PV and BESS) implementations behaved similarly as demand response signals do, potentially increasing economic benefits for DISCOs. In terms of computational efficiency, convex formulations help substantially to reduce computation times, especially if scalability is to be considered when distributed DER installations were studied. [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]

Grid‐connected Single‐Stage Boost Inverters (SSBI) are extensively being researched in the area of photovoltaic energy conversion systems. Owing to their single‐stage boosting capability, this class of power converters results in higher efficiency and reliability. This power circuit configuration is constituted by two mutually dependent sub‐converters, in that a front‐end quasi‐Z‐source (qZS) part is integrated to a back‐end multilevel inverter (MLI). The MLI provides the shoot‐through state to the qZS, while the qZS provides the pulsating DC input to the MLI. In general, solar photovoltaic inverters suffer from the disadvantage of leakage current that flows from solar panels to the grid/load. This paper introduces a dual quasi‐Z‐source based multilevel inverter, which achieves the following benefits: (a) five‐level output voltage, (b) reactive power capability, (c) shoot‐through immunity, (d) continuous input current, and (e) reduced leakage current based on VDE 0126‐1‐1 standards. In this paper, a modified modulation scheme, which is based on the employment of phase‐disposed and level‐shifted carrier signals, has been used to reduce the leakage current. To reduce the leakage current further, a passive filter is employed to eliminate high frequency variations across the parasitic capacitance. The working principle of the proposed power converter and the effectiveness of the modulation scheme have been validated with simulation studies in both standalone and the grid‐connected mode. Finally, the simulation studies are verified through an experimental prototype of 500 W rating. [ABSTRACT FROM AUTHOR]

Summary: This paper presents an overview of the impact of high penetration of photovoltaic (PV) systems in low‐voltage distribution networks (LVDNs). High integration of solar PVs in the LVDNs has severe implications on the system parameters, efficiency, and stability. This paper also introduces the methods that have been driven to overcome these effects to preserve the steady‐state conditions in the system during excessive penetration of PV generation units. A comparison between the contributions and shortcomings of the most recent researches for overvoltage mitigation strategies has been driven. Also, it includes comparing different overvoltage mitigation methods to handle the impact of the overvoltage under high penetration of PV units in the LVDNs. Besides, it presents a comparison between overvoltage mitigation methods based on their pros and cons. [ABSTRACT FROM AUTHOR]

Summary: To carry out the study and simulations of anti‐islanding systems, it is necessary to take into account the generic system proposed by the IEEE 929‐2000 and IEEE 1547 standards, where the network, the RLC load, and PV inverter are connected in parallel to the PCC. The IEEE 929‐2000 standard defines the quality factor to have a standard test condition. The paper presents a modified Active Frequency Drift (AFD) algorithm to detect the islanding of grid‐connected photovoltaic (PV) systems with low harmonics levels without degrading their power factor. Severe issues such as deterioration in power quality and electric shock can occur when a PV inverter operates in islanding mode. Various islanding detection techniques have been investigated in the literature in the last two decades among which, AFD is a typical method. However, a prominent drawback of AFD is its relatively large Non‐Detection Zone (NDZ). The improved AFD method that this paper suggests allows the frequency of the inverter current to be controlled slightly lower (or higher) than the frequency of the terminal voltage. The islanding condition is detected by calculating the changing parameter that relates to the change of the chopping fraction and the line frequency periodically. The frequency deviation is then detected to determine the chopping and a changing parameter, which accumulates to the threshold value when the inverter is shut down. The proposed algorithm overcomes the conventional AFD issues by improving the accuracy of detection, eliminating the NDZ, and reducing the current harmonic distortion. The proposed method is validated with the help of simulated and experimental results of a 350 W PV inverter using IEEE Standards. [ABSTRACT FROM AUTHOR]

Summary: Identifying maximum penetration level (MPL) of Solar Photo‐Voltaic Generation (SPVG) in the distribution system is crucial for system planners and network operators to keep the system parameters within the acceptable limits. This paper provides a systematic and extensive procedure for evaluation of MPL of SPVG and its enhancement methods in distribution systems. More importantly, it illustrates a novel algorithm for affixing the penetration cap of Solar PV. The methodology initially derives a new stability index for locating SPVGs in the system, including both active and reactive power support from SPVGs. The study shows the utility of redefining MPL of SPVGs by considering the reactive power injection through solar inverters also. Deviating from the practice of considering the conventional constraints of voltage rise and maximum loading for MPL estimation, the paper considers loss minimization as the major constraint. The algorithm has potential to identify distributed integration scenario of SPVGs compared to the limited number of placements in the extant algorithms. This paper provides a novel algorithm to evaluate of maximum penetration level (MPL) of solar photo voltaic generation (SPVG) and its enhancement methods in distribution systems. The utility of redefining the MPL of SPVG by considering the reactive power injection through solar inverter is illustrated. The algorithm has distinct advantages over the extant algorithms in identifying a distributed integration scenario. [ABSTRACT FROM AUTHOR]

Background: Recent advancements in solar power generation technology have paved the way for a vast number of photovoltaic (PV) systems integration into the grid network. The global installed capacity of rooftop PV systems has already surpassed a 50 GW mark in 2020, while the total installed capacity of all types of PV systems is reaching beyond 500 GW. The influx of distributed PV‐generators must be equipped with sophisticated control to ensure grid stability, especially during grid faults. A devastating grid outage may occur if the grid‐tied PV inverters are not equipped with the "fault‐ride‐through" mechanism. Many countries have already enforced a mandatory grid code which includes a low‐voltage‐ride through requirements for PV‐generators. Aim and Objective: This paper reviews the design of a rooftop PV inverters in the light of low‐voltage‐ride‐through requirements. Materials and Methods: For the implementation of low‐voltage‐ride‐through (LVRT), the design of low‐voltage‐sag detection, grid‐synchronization, filter‐selection, and power‐controllers are examined through simulations and literature survey. LVRT implementation issues are highlighted with an emphasis on the current controller performance during grid sags. Results and Discussion: From the review and analysis conducted in this study, this paper concludes that ensuring a stable DC‐link and appropriate control‐reference‐signals during the grid faults are the keys to the LVRT implementation. Conclusion: In addition to robust power control, an autonomous PV generator should promptly detect the grid conditions and fulfils the ancillary services like LVRT, anti‐islanding and flicker compensation. The recommendations and the future trends in the LVRT research conclude the review article. [ABSTRACT FROM AUTHOR]

Summary: Commercial two‐stage grid‐connected photovoltaic (PV) inverters suffer from a narrow band maximum power point (MPP) voltage operation. If the voltage falls outside this narrow band, the inverter switches its operation from MPP to power limitation mode. At the same time, these inverters need high start‐up voltages to turn them ON again. The evolutionary algorithms are widely used to track the global MPP at wide input (PV) voltage range. However, the global MPP at low PV voltages cannot be boosted to grid voltage level due to the limited duty ratio of conventional DC‐DC converters that restricts the inverter MPP voltage range. This paper summarizes the potential challenges of narrow range MPP voltage solar inverters under partial shading scenarios. Also, demonstrates a proposed single‐stage negative embedded Z‐source single‐stage inverter (NEZSI) to extend the MPP voltage range. The proposed topology wakes up the inverter at lower threshold voltages that enables it to extract energy from low PV string voltages. In addition, the proposed inverter tracks the MPP at a faster rate with low input current ripple, inrush current, and device stresses. Further in this paper, qualitative and quantitative comparisons between state‐of‐the‐art topologies are provided to highlight the superiority of the proposed inverter. Simulation and experimental validation of the proposed inverter are demonstrated with traditional perturb and observe (P&O) and variable step P&O algorithms. [ABSTRACT FROM AUTHOR]

Remote area electrification is a crucial need in sub-Saharan Africa's drive to attain universal electrification. In Sierra Leone, with a rural population of over 5 million, the electrification rate accounts for less than 10% of the total inhabitants. This paper presents a comparative techno-economic analysis carried out to determine the most feasible of four individual options for off-grid mini-grid power generation system utilizing sources that include: Solar Photo Voltaic (SPV), Diesel Generator (DG), and Battery Storage (BS) system, to provide electricity for a rural and remote village located in the northwestern part of Sierra Leone (longitude 9.1°W and latitude 12.6°N), with an average daily solar irradiance between 4.6 and 6 kWh/m2/day. An assessment of the total electrical load estimated an expected daily consumption of 178 kWh. Simulation, optimization, and sensitivity analyses of each one of the individual power generation systems were carried out using HOMER software. Economic parameters such as Cost of Capital (CC), Net Present Cost (NPC), Levelized Cost of Electricity (LCOE)), technical parameters (energy production characteristics), and greenhouse gases emissions were compared and analyzed. Key findings from the simulation result indicate that systems consisting of DG only ($29,750) and SPV/BS ($110,131) obtained the least and highest CC, respectively. Similarly, in a respective manner, the highest and least NPC were obtained for systems with DG only ($496,336) and PV/DG/BS ($152,491) over a 25-year project lifetime. Furthermore, the least LCOE was obtained for the system comprising PV/DG/BS ($0.336/kWh). With an expected annual generation of (75,121 kWh), PV/DG/BS was obtained to be the most optimal solution. The sensitivity analysis observed that a reduction in the discount rate consequently reduces the LCOE of such a system. Furthermore, the model accounts for a 90% renewable energy fraction, with a significant reduction in the amount of annual GHG emissions, when compared with a generation system using diesel generator only. [ABSTRACT FROM AUTHOR]

This paper considers the problem of tracking the global maximum power point (GMPP) in partially shaded conditions (PSCs) as a multiobjective optimization problem and solves it using a novel multiobjective optimization algorithm on the basis of Bayesian optimization formulation. Bayesian optimization is a metamodel-based global optimization method that is able to balance exploration and exploitation. The Pareto solutions are obtained by using a multiobjective Bayesian optimization algorithm. Also, a new acquisition function is proposed to improve the diversity and convergence of the Pareto solutions. Two objective functions are introduced to remove the large tracking errors and oscillations of the operating point around the GMPP. The suggested method is implemented online for GMPP tracking so that the suggested method monitors any change in environmental conditions and generates the optimal duty cycle for the DC-DC converter for the GMPP tracking (GMPPT) by the PV array. Several multipeak PSC scenarios are implemented and simulated to show efficiency of the suggested approach. The MATLAB/SIMULINK is employed to implement a photovoltaic (PV) system comprising a PV array, a boost converter, and the proposed multiobjective Bayesian optimization algorithm (MOBOA). The simulation results show a very satisfactory performance of the MOBOA in terms of transient state and steady-state oscillations and tracking speed. [ABSTRACT FROM AUTHOR]

To alleviate the issues of global warming and energy crisis, countries are vigorously developing renewable energy technology. The integration of large-scale renewable energy, including wind energy, hydropower, and photovoltaic (PV), has a great impact on system operation scheduling and economic dispatch. This paper presents an economic dispatching method of wind-PV-CSP-hydro-battery system with wind and photovoltaic power generation as the main energy sources. The long short-term memory (LSTM) neural network is applied to predict wind and PV power, besides, the Latin Hypercube Sampling (LHS) method and the synchronous reduction algorithm are used to obtain 10 typical wind and PV power scenarios. A day-ahead economic dispatch model of wind-PV-CSP-hydro-battery mathematical model is established, and relevant constraints are considered. Concentrated solar power (CSP), hydropower stations, batteries, and transferable loads are used as flexible resources to increase the penetration rate of wind and photovoltaic power generation. Finally, three cases are tested to demonstrate the feasibility of the proposed model. The results show that: (1) LSTM neural network can well predict the output power of wind and photovoltaic power generation with a small root mean square error (RMSE). (2) The introduction of transferable loads and CSP power station into the renewable energy power system can effectively reduce the fluctuation and curtailment rates of wind power and PV power generation. [ABSTRACT FROM AUTHOR]

Background: With the increase in demand for generating power using photovoltaic systems (PVs), bidirectional converters for energy storage in these systems have become a major challenge. Reducing the losses and the operation complexity are the main aims in designing the bidirectional converters. Purpose: This paper explores how the voltage gain of bidirectional converters improves, increasing in the boost mode and decreasing in the buck mode. It also describes how the efficiency is increased by providing soft switching conditions for all semiconductor elements. Design/Method: In this paper, a new ZVS bidirectional DC‐DC converter with high conversion ratio is proposed. In the proposed converter to achieve soft switching condition for each direction, a separate auxiliary switch is used, which provides ZVS condition for the main switches, therefore, the converter efficiency is increased. Additional auxiliary switches are switched as the complements with the main switches, therefore, the operation of the converter is simple and the complex control circuit is not required. To improve voltage gain, coupled inductors and series capacitors in the power path have been used. Results: The proposed converter has low voltage stresses in both directions, so, low‐voltage power MOSFETs with low RDS(on) can be used in the converter. Also, due to the creation of soft switching condition on the switches, the proposed converter has low EMI noise compared to the conventional one. A 100 W prototype of the proposed converter is implemented, and the experimental results are presented to confirm the theoretical analysis. The proposed converter under full load has a 96.5% efficiency and EMI noise has been obtained by a decrease of 11dBμv in comparison with the conventional one. Conclusions: This paper helps the reader to learn how to the increase voltage gain and efficiency in bidirectional converters. It also presents new technique to provide soft switching condition and improving voltage gain with minimum elements in non‐isolated bidirectional converters. [ABSTRACT FROM AUTHOR]

Common-mode current is one of the major challenges in transformerless grid-connected photovoltaic (PV) inverters. This current is affected when the PV arrays are exposed to different environmental conditions and its value increases. This paper attempts to investigate the effect of mismatched condition on voltage balance of PV arrays, which leads to the increment of common-mode current. A new circuit structure is presented for compensating for voltage drop caused by partial shading and ambient temperature and removing the effect on the common-mode current. To validate the proposed structure, a laboratory prototype of this circuit is implemented. [ABSTRACT FROM AUTHOR]

Computer models designed to assess harmonic levels created by renewable energy sources (RESs) need to reproduce the converter operation effect. However, only a few simplified time‐domain models have been developed to predict harmonics while reducing simulation time, which is one of the main limitations of detailed models. This paper presents a novel time‐domain model, called the harmonic average model (HM), to estimate harmonic currents generated by inverters. The superposition principle is applied to include dead time and switching effects in the average model. In addition, the snubber effect is considered by introducing snubber circuits in the HM. Time‐domain simulations of a type‐IV wind turbine are executed with existing models and then with the HM to evaluate the proposed model. Field measurements in a wind power plant and in a photovoltaic plant are used to validate the HM under different power injection scenarios. The results indicate that the HM follows reference currents while accurately estimating the harmonic spectra. Further, the HM is relatively simple to deploy and reduces computation time. A comparison between the HM results and field measurements suggests that the simulated spectra are an adequate approximation of the measured spectra. These results confirm that the HM can be used by transmission system operators to support the prediction of harmonic currents generated by inverters and to estimate the impact of RESs on voltage quality. [ABSTRACT FROM AUTHOR]

Summary: Review transcript presents copious solar tracking methods to investigate their output potential and also outline tracker type, construction, cost, and design parameter. The solar follower systems encompassed five classifications based on the tracking methods are active, passive, semi‐passive, manual, and chronological tracking are also reviewed with their application and feasibility. These all method‐based research paper are compared on the basis of complexity of circuit, cost, tracking based on (radiation or astronomical equation), degree of freedom, control strategy, accuracy, energy intact, power or energy gain, tracing error, and panel efficiency. Basically, one axis and two axis sun following system review revels compare study against stable system which addressed their suitability and capability of maximum energy generation and MPPT technologies. [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]

In recent years, the emerging of renewable energy resources (RERs) in distribution networks has been rapidly raised by network planners. Although the integration of RERs brings a lot of advantages to distribution networks, they impose some disadvantages such as high initial capital investment on distribution companies (DISCO). This paper proposes a new two‐stage multi‐period distribution network expansion planning (DNEP), in which the potential of private investor's (PIs) participation is considered in the problem. In the proposed model, the planner presents an incentive price to buy energy from PIs so that it attracts them to participate in the planning projects. This incorporation is based on a long‐term contract that guarantees the benefits of both contract correspondents. The proposed model is presented as a hierarchical two‐stage optimization problem where the upper stage determines the general structure of the system and the lower level considers the operational conditions. Moreover, the photovoltaic plants (PVs) and energy storage systems (ESSs) are investigated as clean and new technologies in the planning, and DISCO determines the optimal sizing and sitting of these resources regarding technical and economical assessments. The fuzzy clustering method (FCM) is used to capture the intermittency of the system loads and solar irradiance by creating a day‐ahead scheme. The effectiveness of the proposed DNEP problem is evaluated through a 54‐bus distribution test system and a real 104‐bus test system as well. Simulation and economic results show that how PIs can play an important role in long‐term planning by investing RERs. [ABSTRACT FROM AUTHOR]

This paper presents a novel hybrid approach combining Gramian Angular Summation Field (GASF) method with a convolutional neural network (CNN) to classify power quality disturbances. Firstly, a 1‐D Power quality disturbance signal is transformed into a 2‐D image file using GASF. Subsequently, CNN is implemented for features extraction and image classification. In this work, the synthetic power quality (PQ) disturbances are considered including nine single disturbances and five mixed disturbances. Further, to capture multi‐scale aspects of power quality disturbances problem and reduce overfitting, a unit is designed using 2‐D convolutional, pooling, and batch‐normalization layers. The classification study is further supported by experimental signals obtained on a prototype setup of PV system. The obtained results demonstrate the efficiency and reliability of the proposed method. The proposed method is compared with the other advanced CNNs and other conventional methods to illustrate its effectiveness. [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]

According to increasing growth of DC loads, DC microgrids (MGs) have an effective role in future power systems. Improvement of power management is one of the important issues in DC MGs. In this paper, in order to provide an accurate power management in standalone low‐voltage DC (LVDC) MG, including photovoltaics (PVs) and battery energy storage systems (BESSs), an AC component is superimposed to the output voltage of DC‐DC converters by inspecting the frequency droop control of the synchronous generators. In addition, two corrective terms based on the calculation of AC active and reactive powers are added to this AC component, which is named improved frequency droop method (IFDM). Different operating modes for PV system comprising maximum power point tracking (MPPT) and voltage control mode (VCM); and BESS consisting of charge, discharge, and idle are considered in the proposed power management scheme based on the state of charge (SoC) of local BESS. On the other hand, the conventional proportional‐integral (PI) controllers in DC‐DC converters' control structure present poor transient dynamic performance and low loading level. Hence, fractional order PI (FOPI) controllers are designed by optimization of integral time absolute error (ITAE) criteria. The effectiveness of the proposed FOPI controllers combined with IFDM scheme is evaluated by simulations conducted in MATLAB/SIMULINK software. The FOPI‐IFDM approach provides accurate current sharing and better voltage regulation without dependence on communication link in comparison with PI‐IFDM under load, line impedance, and solar irradiance variations. [ABSTRACT FROM AUTHOR]

Summary: In this paper, a three‐phase single‐stage grid‐connected photovoltaic (PV) system with active power filtering capability by means of a three‐level T‐type inverter is presented. The system is intended to fulfill many functions: harmonic mitigation, unity power factor operation, maximum power extraction from PV source, and so on. For the proposed system to achieve these tasks with a good dynamic performance, a new control strategy based on the fuzzy logic controller is developed. Fuzzy control has three main stages and each one requires many settings or selection of parameters. A new approach of setting the scaling factors which considerably affect the system's response is proposed. Furthermore, a methodology to properly set the fuzzy rules is suggested. The electrical power chain of the system comprises a farm of a PV source, three‐level T‐type inverter space vector pulse width modulation controlled, inductor filter, non‐linear load, and the utility grid. To evaluate the performance of the proposed control, a processor‐in‐the‐loop is performed as a hardware verification of the inverter control algorithm using a low‐cost STM32F4 discovery board, while the power circuit plant is modeled in the host computer using Matlab/Simulink. The obtained results are very satisfactory and confirm the role of each component, especially in terms of maximum power tracking, power quality, unity power factor operation, and control robustness. [ABSTRACT FROM AUTHOR]

Summary: This paper presents an auto‐tuned Incremental Conductance (Inc) maximum power point tracking (MPPT) algorithm for a photovoltaic (PV) system. Proposed MPPT algorithm is adaptive in nature in terms of both MPPT perturbation frequency and step‐size based on the change in PV voltage. To verify the functionality of the proposed adaptive frequency adaptive step‐size Inc MPPT method, a boost converter based PV setup is developed and the algorithm is implemented in Arduino Mega‐2560 micro‐controller. An extensive comparative result analysis of the proposed technique is done with the conventional fixed frequency variable step‐size Inc MPPT algorithms which are based on power‐voltage slope and change in power. The proposed change in PV voltage based adaptive frequency adaptive step‐size algorithm improves both steady‐state and dynamic performance compared to the conventional fixed frequency variable step‐size Inc algorithm. The steady‐state oscillation is low with a faster tracking response. [ABSTRACT FROM AUTHOR]

Summary: It is known that the demand for renewable energy systems during recent years has increased significantly, especially for wind and photovoltaic systems. The continuous improvement of the efficiency and performance of these systems is important to their growth, particularly in terms of harvesting the maximum power. Many types of methods and techniques are available for tracking the maximum power point, the most important of which is the concept of artificial intelligence. Artificial intelligence (eg, neural networks and fuzzy neural networks) has great potential to handle complex systems or those that have non‐linear parameters and are influenced by environmental conditions. In this paper, artificial intelligence is used to predict the optimal reference values for wind turbines and photovoltaic panels used in maximum power point tracking (MPPT). Neural networks were used in the wind turbine system, while fuzzy neural networks were used in the photovoltaic systems. The networks were trained in real‐time using an incremental training mode based on the back‐propagation algorithm. The proposed system was designed practically based on the microcontroller and has been tested, and the results are extracted in real‐time. The results have proven their effectiveness and conformity with the required optimal values. [ABSTRACT FROM AUTHOR]

Summary: Varying solar radiation on photovoltaic (PV) panels reduces the PV system's output and increases the mismatch losses. Several techniques have been proposed to solve the mismatch problem, for example, the reconfiguration technique of PV panels. Most of the reconfiguration techniques have been proposed for small systems because of the difficulty in applying to large systems as a large number of switches are required for such applications. In this paper, a new technique based on total‐cross‐tied (TCT) in two reconfigurable stages is proposed. In the first stage, the shading over the PV plant is dispersed by switching between arrays. In the second stage, the shade dispersion from the first stage is increased by optimizing between the columns. The number of switches and sensors were reduced by using genetic algorithm, thus reducing the system cost. To demonstrate the proposed new reconfiguration technique, four shaded cases were simulated and tested using MATLAB/SIMULINK. A comprehensive analysis of power–voltage (P–V) curves and row currents calculation was performed, for TCT configuration and the proposed new reconfiguration technique. Also, a comparative study on performance analysis, energy‐saving, and income generation was carried out for each shading case. The comparative study of the four cases shows that the reconfiguration techniques proposed in two stages generate more power under partial shading conditions than TCT. Further research is needed to ensure the practicality of the switches needed to realize this technique. [ABSTRACT FROM AUTHOR]

Summary: An effective peak current‐limiting control strategy is presented in this paper, for improved dynamic performance of a grid‐connected photovoltaic (GCPV) inverter under unbalanced grid voltages. A simple analysis is developed for calculating the rated inverter power under unbalanced grid voltages without tripping the PV inverter for reliable operation. The active power oscillations induced due to the unbalance in the grid voltages are minimized by equating the active power oscillating terms to zero in the reference current generation. The prime focus of this work is on estimating the reference currents and limiting the inverter currents to rated value and providing low‐voltage ride‐through capability by judiciously balancing positive and negative sequence currents. A prototype hardware is developed in the laboratory and the proposed control scheme is implemented using dSPACE 1103 real‐time controller board. A solar simulator has been used to replicate the PV array. The simulation (MATLAB/Simulink) and the experimental results establish that the proposed controller scheme effectively minimizes the oscillation in active power and limits the inverter currents. [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: In this paper, an improved fractional order notch filter (IFONF)‐based grid‐forming inverter control scheme is employed to mitigate the harmonics in photovoltaic system applications. Moreover, a fuzzy gain tuning proportional‐integral‐derivative (FTPID) controller is developed for the dc‐link voltage to maintain its reference value. The proposed FTPID‐IFONF control scheme is executed to evaluate the active fundamental weight components (FWC) of the load currents and distorted grid voltages consequently generates the PWM pulses to the grid‐forming inverter for power quality enrichment in a grid integration with photovoltaic applications. The integer order based filters have some constraints due to differentiator term and fixed integrator. For this reason, an improved design of an integer order notch filter is suggested in the proposed FTPID‐IFONF controller scheme. The behavior of the proposed FTPID‐IFONF control scheme is found good in‐terms of elimination of dc offset, grid‐synchronization, separation of fundamental components, adaptive behavior and harmonic elimination at the consumer terminals. The proposed controller is validated under several load and grid dynamic conditions such as steady‐state, grid voltage sag‐swell, distorted, load dynamic and removed conditions on MATLAB/Simulink platform. A prototype PV integrated with grid setup is constructed to validate the proposed system in the real‐time. The FTPID‐IFONF control scheme is well justified under several grid and load dynamic conditions and the harmonic distortions of the grid characteristics are found well based on the limits of IEEE‐519 standards. A comparative study is also analyzed to show the effectiveness of the controller with recently published works. [ABSTRACT FROM AUTHOR]

Summary: Hybrid renewable energy systems (HRES) are proving a promising solution for rural electrification in India, where grid power availability is limited. This paper aims to identify the optimal design and pre‐feasibility techno‐economic analysis of the hybrid grid‐independent renewable system for rural electrification. The proposed hybrid system integrates the various renewable energy system configurations to provide continuous power for the electric load demands of Kanakadri palle village, Andhra Pradesh, India. HOMER software is utilized to design the proposed hybrid system, perform optimization, techno‐economic analysis, and simulation. Here, six different hybrid system configurations were taken into account to perform a comparative economic analysis. The results obtained shows that one of the hybrid systems, PV/DG/converter/battery system (120 kW‐PV modules, 54 kW‐DG, 200 number of batteries with 260 Ah ratings, and 50 kW‐power converters), is the least economical optimal system based on least net present cost and Levelized cost of energy (COE), highest renewable fraction, and zero unmet electric loads percentage (NPC: $341 280, COE: $0.217, highest renewable fraction: 96.6% and unmet electric loads: 0%). For the site considered, this optimal hybrid system can provide a reliable power supply to the total energy requirements of 332.97 kWh/d and achieve 75.68% carbon emission reduction compared to a diesel generator. Moreover, the comparison of different system configurations was carried out based on economic analysis. This analysis shows that proposed hybrid system can be an appropriate model to provide reliable power at a low generation cost for the village considered in this study and can be recommended for future electrification projects. [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: The supercapacitors (SCs) are suitable for short‐term fast power regulations, while the batteries are suitable for long‐term slow energy management of microgrid (MG). As SCs and batteries complement each other's deficiencies, the SC‐battery hybrid energy storage systems (SBHESS) have been commonly used for mixed applications of fast transient and slow long‐term power regulations. The SC reduces the stress of fast power variations on the battery, which prolongs its lifetime. However, it increases the cost of the energy storage in comparison to the case that battery is just used. Therefore, the drawback of SBHESS is its increased cost. The sizes of SC and its converter, which directly determine their costs, should be enough to handle primary frequency control (PFC) in the worst cases of shortage and surplus power generation that the MG ever experiences. In this paper, the potentials of Photovoltaic (PV) systems, smart LED lighting loads (SLEDLLs), and thermostatically controlled loads (TCLs) in PFC is used to decrease the participation share of SC in the PFC and hence decrease the sizes and costs of SC, and its converter. The simulation results show that with the coordination of SBHESS, SLEDLLs, PVs, and TCLs, the required sizes of SC and its converter are decreased by 64% and 50%, respectively. Also, for a 10‐year period operation, the total cost of SC and its converter is decreased by 51.5%. [ABSTRACT FROM AUTHOR]

Summary: This paper presents photovoltaic (PV) systems modeling and fault analysis with solar energy fluctuation to discuss maximum fault current profiles. The modeled PV farm is arranged with series and parallel PV modules to offer 6.5 kV power. Two‐level 3‐phase voltage source inverter (VSI) and dc‐dc boost converter are used for all PV systems with LCL filter. A current control strategy using synchronous rotating frame method is implemented with park transformation approach. Average and aggregate models give inaccuracy, which this paper overcomes with accurate isolated single PV system, and PV‐dominated feeder. Pulse width modulation and sinusoidal pulse width modulation techniques are applied. Incremental conductance maximum power point tracking technique is used to extract PV maximum power. Phase locked loop technique for grid synchronization and proportional integral voltage control technique are also applied. Here, the maximum fault current corresponds to the maximum phase current at specified time. This simple and effective method is applied on PSCAD software simulations to collect the data. Discussions on obtained results showed short‐time irradiation fluctuation impacts on fault current profiles and argue on related aspects. The data comments and explanations to address analyzed protection challenges with PV penetration in distribution system are very promising. [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: Objectives: This paper explores the performance of the Single Machine Infinite Bus (SMIB) power system integrating a Photovoltaic (PV) generator when compensated by the Thyristor Controlled Series Capacitor (TCSC) and the Static Synchronous Series Compensation (SSSC) Flexible Alternating Current Transmission System (FACTS) devices. Method: The analysis is performed after the introduction of a step change in the mechanical input and excitation voltage of the synchronous generator connected in parallel with the PV generator at different levels of solar intensity. Time domain simulations based on a non‐linear dynamic mathematical model are used for numerical simulations. Results: The simulation results demonstrated the effectiveness of the addition of TCSC and SSSC FACTS devices to improve the power transfer capacity of the SMIB power system with a PV generator. Conclusion: The response of TCSC and SSSC is almost similar. Nevertheless, the introduction of the two FACTS devices does not achieve a system stable operation at 50% of the total level of solar irradiance. TCSC is more effective than SSSC in maintaining the stability of the system. [ABSTRACT FROM AUTHOR]

Summary: In this paper, we study an integrated unit commitment and natural gas network operational scheduling with renewable energy (wind and photovoltaic power plants) which changes the load curve to a duck curve. Wind and photovoltaic energy are both uncertain in nature. The availability of photovoltaic energy at certain times of day changes the pattern of the load. This load curve which is called "Duck Curve," raises the question of whether the power system could provide the necessary ramp rate and capacity for full utilization of photovoltaic energy. The use of gas power plants to deal with the sharp ramp rate would have a negative impact on the flow of gas in the gas network. That is, the uncertain output of renewable resources requires the flexibility of gas power plants which affects the gas network. Storage devices of electricity and gas, line‐pack and the technology of electricity to gas transformation (P2G) could be effective solutions for reducing fluctuations and ensuring reliable operation of electricity and gas networks. The underlying problem is known to be a complex nonconvex problem. Compared to existing modeling and solution methods, we propose some efficient reformulation which enables us to rewrite the problem as a convex mixed integer program using Benders decomposition. Given the convex reformulation, we can solve the resulting convex model to optimality. We demonstrate the effectiveness of the proposed method by solving some standard examples such as the modified IEEE 24‐Bus test system and the Belgian 20‐node gas network. [ABSTRACT FROM AUTHOR]

Summary: In this paper, optimized controller design for multiple distributed generators (DGs) based microgrid network is discussed, where IEEE 1547 standards are followed for primary photovoltaic DG. According to standards, the primary photovoltaic/auxiliary battery energy storage system is integrated through voltage source converter's feedback controller, with operational modes: active reactive (P − Q) power control for grid synchronized operation and voltage frequency (V‐f) droop control for islanded microgrid. To overcome the inadequacy of conventional controller tuning in a multiple DGs‐based weak microgrid architecture, a new mutation based improved firefly algorithm is proposed in this paper. The worst stability operation is considered for voltage source converter's P‐Q and V‐f coordination during insufficiency in battery energy storage system management. The effectiveness of the proposed technique is validated on MATLAB Editor/ Simulink platform. Further, a hardware‐in‐loop test bench validation is achieved by TMS320 C6713 based DSP Starter Kit and embedded MATLAB coder. [ABSTRACT FROM AUTHOR]

Summary: In this paper, a novel photovoltaic‐tied unified power quality conditioner (PV‐tied UPQC) scheme is proposed for elimination of major current‐ and voltage‐related power quality issues present in the distribution system. Photovoltaic‐tied UPQC topology is completely new in its category of photovoltaic grid integration. Although advanced UPQC schemes have been discussed in literatures, but concepts related to PV‐tied UPQC are few in number to discuss elaborately about elimination of power quality issues. In this paper, a new PV‐tied UPQC topology with an improved LCL filter at shunt inverter part is proposed, which provides better compensation to current quality issues. This paper also proposes a novel model reference tracker control law to improve power quality and elimination of current harmonics, voltage sag/swells, and unbalance. It has feature to regulate tracking error between model reference signal and actual measured signal. Therefore, proposed model reference approach provides robustness and flexibility for various operating conditions. In addition, integral plus sliding mode controller has been used for better control of dc‐link voltage to deal with severe change in power system conditions. Performance and efficiency of present topology with novel controller is analyzed along with conventional controllers through laboratory developed prototype, controlled by DS1103 dsp processor. [ABSTRACT FROM AUTHOR]

Summary: The addition of photovoltaic (PV)‐based distributed generators introduces several challenges to power system protection and control engineers. In a multi‐source distribution network, power flow becomes bi‐directional, and conventional overcurrent and earth fault protection schemes are threatened. Addition of PV‐based distributed generation could lead to protection blinding, sympathetic tripping, and loss of coordination in conventional overcurrent protection. This paper evaluates the general concerns regarding protection in a PV‐based distributed generation network, by modeling a power system with sequence networks for different types of faults. The power system is simulated with Digsilent PowerFactory. The results show that many of the general concerns can be mitigated by using sequence components to identify faults. A method is presented to adapt conventional overcurrent protection schemes without the need for communication‐assisted protection. [ABSTRACT FROM AUTHOR]

Summary: Recently, the partial shading conditions (PSCs) and its impact on the performance of photovoltaic (PV) systems have motivated to explore novel approach to minimize the PSC adverse effect. In this context, the existing PV arrays are reconfigured to overcome the effects of PSCs. This paper presents a comprehensive and comparative study of existed total cross‐tied (TCT) configuration with a novel Latin square puzzle‐based TCT configuration called Latin square‐TCT (LS‐TCT) to minimize the shading effects. An investigation is carried out based on the considered partial shading patterns (progressive bottom to top, left to right, diagonal, multistory building, and zigzag shading cases) in global maximum power point (GMPP), power loss, and fill factor. The performance of LS‐TCT configuration is compared with benchmark TCT configuration. It is noticed that the proposed LS‐TCT configuration has maximum power of 2279 W as compared with 1976 W for TCT configuration at global maximum power point for a shading case. Further, it is also shown that the minimum power losses in proposed LS‐TCT configuration are reduced to 330 W as compared with 633 W for TCT configuration. Moreover, the fill factor in the proposed LS‐TCT configuration is 9.91 as compared with 8.59 for TCT configuration under the considered PSCs. Overall, the performance of LS‐TCT configuration is found to be superior as compared with TCT configuration. [ABSTRACT FROM AUTHOR]

Solar energy is effectively used to power stand-alone photovoltaic pumping systems (PVPSs) for irrigation and drinking purposes in remote areas. However, random vicissitudes and the unpredictability of the amount of solar energy that can be harnessed lead to difficulties in designing PVPS. Thus, an optimal sizing approach is essential to ensure satisfactory performance. In this paper, a numerical iterative sizing approach based on technical and economic objectives is developed to optimize the configuraion of PVPS. The loss of load probability criteria is considered as the technical objective, while the life cycle cost criteria is considered as the economic objective. The proposed pumping system provides a daily water for a small village in Kuala Lumpur, Malaysia. The proposed sizing approach is used to test all the possible configurations of a wide range of photovoltaic (PV) array sizes to specify the PV array configurations that realize the reliability condition. The optimal size of the storage tank and the optimal number of PV modules connected in series and parallel are specified to keep up a balance between the loss of load probability, life cycle cost, and excess water volume of PVPS. The performance of the system is tested on the basis of the proposed optimal configuration and hourly meteorological data for 1 year. The results show that the proposed system is available throughout most of the year. [ABSTRACT FROM AUTHOR]

Regulating the voltage of distributed renewable power systems is a main technical problem of power system controllers. This paper proposes a new method to design the controller of double-input direct current-direct current converters which are applied in hybrid renewable power systems. In addition, in this research, the converter has novel topology and can be used to obtain well-regulated output voltage from 2 renewable energy sources, and the suggested structure has important advantages compared with previous ones. The operating principle and design criteria of the designed converter are provided. Furthermore, the conventional controllers cannot set the voltage of hybrid power systems at some critical situations. At the other part, on the basis of the multivariable control strategy, an efficient controller for the converter is designed. In the last part, on the basis of simulation study and several experiments, converter performance in different conditions is analyzed and the efficiency of the designed converter and multivariable controller is approved. [ABSTRACT FROM AUTHOR]