Genetic Algorithm-based Model Predictive Control for Partial Shading Mitigation on PV Array

Photovoltaic (PV) system output power greatly depends on environmental operating conditions. Partial shaded condition (PSC) operates PV string under mismatch. PV module mismatch has been one of the major causes for reduced amount of output power. Maximizing the amount of energy extraction from PV system under mismatch greatly influenced by conversion efficiency as well as the mismatch mitigation topology used. Differential power processing (DPP) is one of the advanced techniques to deal with mismatch conditions and enhance power output from a PV system. In this paper hybrid modular DPP topology is presented. The proposed technique mitigates the effect of mismatches at submodule and enhance power extraction from PV string. Since in majority shading on a PV module is nonuniform. The conversion efficiency of module level DPP shading mitigation techniques enhanced using submodule level DPP architecture. To demonstrate its applicability simulation study is carried out in MATLAB Simulink and results are compared with traditional bypass method and module level DPP. Simulation results showed the reduction in mismatch loss and improvement in efficiency and power output.

Partial shading conditions (PSCs) can significantly reduce the output energy produced by photovoltaic (PV) systems. Moreover, when such conditions occur, conventional and advanced maximum power point tracking (MPPT) systems fail to operate the PV system at its peak because the bypassing diodes may cause the PV system to become trapped at a low power point when they are in conduction mode. The PV system can be operated at the global maximum power point (MPP) with the help of global peak searching tools. However, the frequent use of these tools will reduce the output of PV systems since they force the PV system to operate outside its power region while scanning the I-V curve in order to determine the global MPP. Thus, the global peak searching tools should be deployed only when a PSC occurs. In this paper, a simple and accurate method is proposed for detecting PSCs by means of monitoring the sign of voltage changes (positive or negative). The method predicts a PSC if the sign of successive voltage changes is the same for a certain number of successive changes. The proposed method was tested on two types of PV array configurations (series and series–parallel) with several shading patterns emulated on-site. The proposed method correctly and timely identified all emulated shading patterns. It can be used to trigger the global MPP searching techniques for improving the PV system’s output under PSCs; furthermore, it can be used to notify the PV system’s operator of the occurrence of PSCs.

The power output of a photovoltaic (PV) system is inherently dependent on climatic factors. To maximize the energy harvested from PV arrays, maximum power point tracking (MPPT) algorithms are employed. These algorithms dynamically adjust the operating point of the system to extract the maximum available power. However, under partial shading conditions (PSCs), conventional MPPT algorithms often fail to locate the global maximum power point, leading to suboptimal power extraction. In this study, a robust MPPT technique based on sliding mode control (SMC) is proposed to enhance tracking efficiency and optimize power extraction from PV arrays under PSC. Particle swarm optimization (PSO) is incorporated into the MPPT framework, enabling the dynamic tuning of SMC parameters for improved adaptability and performance. The proposed SMC structure is designed to regulate the duty cycle of a boost converter, ensuring effective power conversion. The system is simulated in Matlab/Simulink for various PSCs. The simulation results demonstrate that the PSO-tuned SMC methodology exhibits superior tracking performance, enabling the PV system to rapidly and accurately converge to the true MPP under varying weather and shading scenarios. The findings indicate that the proposed technique enhances the efficiency and reliability of PV energy harvesting in PSCs.

Monthly energy yield assessment of solar photovoltaic system under uniform irradiance and partial shaded condition

The expanding use of photovoltaic (PV) systems as an alternative green source for electricity presents many challenges, one of which is the timely diagnosis of faults to maintain the quality and high productivity of such systems. In recent years, various studies have been conducted on the fault diagnosis of PV systems. However, very few instances of fault diagnostic techniques could be implemented on integrated circuits, and these techniques require costly and complex hardware. This work presents a novel and effective, yet small and implementable, fault diagnosis algorithm based on an artificial intelligent nonlinear autoregressive exogenous (NARX) neural network and Sugeno fuzzy inference. The algorithm uses Sugeno fuzzy inference to isolate and classify faults that may occur in a PV system. The fuzzy inference requires the actual sensed PV system output power, the predicted PV system output power, and the sensed surrounding conditions. An artificial intelligent NARX-based neural network is used to obtain the predicted PV system output power. The actual output power of the PV system and the surrounding conditions are obtained in real-time using sensors. The algorithm is proven to be implementable on a low-cost microcontroller. The obtained results indicate that the fault diagnosis algorithm can detect multiple faults such as open and short circuit degradation, faulty maximum power point tracking (MPPT), and conditions of partial shading (PS) that may affect the PV system. Moreover, radiation and temperature, among other non-linear associations of patterns between predictors, can be captured by the proposed algorithm to determine the accurate point of the maximum power for the PV system.

One of the main problems with a solar photovoltaic (PV) system is the partial shading condition (PSC).This results in a significant reduction of the output power of a solar PV system.This paper mainly aims at proposing and validating a novel optimization technique namely the Genetic Algorithm (GA) for Maximum Power Point Tracking (MPPT) in case of PSC.In this study, an experimental examination utilizing a PV emulator highlights the effect of PSC on PV system performance.PSC was found to result in a 37% decrease in maximum power, a 38% decrease in fill factor, and a 60% decrease in efficiency.Metaheuristic techniques for P-V curves with several peaks can be used to track the maximum power point (MPP).GA is based on a metaheuristic methodology that has been applied to solve optimization problems in a variety of systems, such as PV systems with MPPT.With a convergence time of less than 2 ms, the suggested system can track the global MPP with 99% tracking efficiency.This demonstrates the improvement in tracking time and accuracy over traditional MPPT techniques.Additionally, the suggested system can also accomplish steady operation in dynamically changing environmental conditions and reduce the oscillations around MPP.

INTRODUCTION: Significant advances have been made in photovoltaic (PV) systems, resulting in the development of new Maximum Power Point Tracking (MPPT) methods. The output of PV systems is heavily influenced by the varying performance of solar-facing PV panels under different weather conditions. Partial shading (PS) conditions pose additional challenges, leading to multiple peaks in the power-voltage (P-V) curve and reduced output power. Therefore, controlling MPPT under partial shading conditions is a complex task. OBJECTIVES: This study aims to introduce a novel MMPT algorithm based on the ant colony incorporated bald eagle search optimization (AC-BESO) method to enhance the efficiency of PV systems. METHODS: The effectiveness of the proposed MPPT algorithm was established through a series of experiments using MATLAB software, tested under various levels of solar irradiance. RESULTS: Compared to existing methods, the proposed AC-BESO algorithm stands out for its simplicity in implementation and reduced computational complexity. Furthermore, its tracking performance surpasses that of conventional methods, as validated through comparative analyses. CONCLUSION: This study confirms the efficacy of the AC-BESO method over traditional strategies. It serves as a framework for selecting an MPPT approach when designing PV systems.

This paper presents the modelling and analysis of photovoltaic (PV) array under partial shading conditions. The characteristics of PV array have been studied under different shading conditions. The simulation model of the PV array has been designed through MATLAB simulation. Detailed analysis of the effect of partial shading and location of local maxima in power-voltage curves has been studied. This study builds the theoretical knowledge of the researchers to identify the location of local maxima points of the PV array under partial shading conditions.

Tie failure detection technique for total cross tied solar photovoltaic system

In this paper, detailed studying of the effect of partial shade on Photovoltaic (PV) arrays, which represent one of the most well-known problem that affect this field of renewable energy, because of that matter, this paper discuss this issue and make a detailed discussion for different connection topologies that used to increase the efficiency of the PV system under Partial Shade. This paper using MATLAB/Simulink to analyze three different connection topologies of PV modules under partial shade conditions (PSC), these topologies are the Series-Parallel connection (SP), Total-Cross-Tie (TCT), and Bridge-Linked (BL).The results in the study help the workers in this field to choose the best connection topology for PV power system and reach to that; the Total-Cross-Tie (TCT) topology is the best.

Because of the unpredictable activity of solar energy sources, photovoltaic (PV) maximum power point tracking (MPPT) is essential to guarantee the continuous operation of electrical energy generation at optimal power levels. Several works have extensively examined the generation of the maximum power from the PV systems under normal and shading conditions. The fuzzy logic control (FLC) method is one of the effective MPPT techniques, but it needs to be adapted to work in partial shading conditions. The current paper presents the FLC-based on dynamic safety margin (DSM) as an MPPT technique for a PV system to overcome the limitations of FLC in shading conditions. The DSM is a performance index that measures the system state deviation from the normal situation. As a performance index, DSM is used to adapt the FLC controller output to rapidly reach the global maxima of the PV system. The ability of the proposed algorithm and its performance are evaluated using simulation and practical implementation results for single phase grid-connected PV system under normal and partial shading operating conditions.

Although proliferation of photovoltaic systems in power systems have caused some problems such as decreasing overall inertia, intermittency and etc., they have shown to have the potential to help improve power systems operation. For instance, photovoltaic systems have been proposed to provide frequency response. Previous research studies focusing on this subject have assumed photovoltaic systems with being subjected to shading conditions which is wrong. To fill this gap, this paper intends to investigate the effect of partial shading on the photovoltaic systems and propose a novel approach to enable photovoltaic systems to provide frequency response even under partial shading conditions. The simulation results prove the accuracy and efficiency of the proposed approach, being capable of enabling the photovoltaic systems to provide frequency response under normal (not shading) and partial shading conditions.

Photovoltaic module is very susceptible to partial shading problem. In a photovoltaic power system, large number of photovoltaic modules are connected in series to provide required voltage and power. Due to large number of photovoltaic modules, the chances of every photovoltaic module to receive uniform solar irradiance become lower. Therefore, a photovoltaic system consists of large number of photovoltaic modules is even more susceptible to partial shading problem. This paper presents the investigation of the energy yield of a photovoltaic system under partial shading conditions. The investigation results shows that the energy yield of a photovoltaic system decreases as the shading heaviness increases. However, the effect is not constant. The effect is especially significant when the photovoltaic system is under lightly partial shaded conditions. In worst case, the energy yield of the photovoltaic system can drops up to 17.65 % as the shading heaviness increases by 20 %. Therefore, the partial shading need to be address in order to minimize the losses of the photovoltaic system under partial shading conditions.

The performance of the Photovoltaic (PV) array is greatly hampered by Partial Shading Conditions (PSCs). The output power and efficiency of the PV array degrades substantially under PSC. The main objective of this research paper is to compare, simulate and analyse the performance of conventional hybrid PV configurations, namely Series Parallel-Total Cross Tied (SP-TCT), Bridge Link-Total Cross Tied (BL-TCT), Honey Comb-Total Cross Tied (HC-TCT) and Bridge Link-Honey Comb (BL-HC) with proposed novel hybrid PV configurations, such as Alternate-Total Cross Tied-Series Parallel (A-TCT-SP), Alternate-Total Cross Tied-Bridge link (A-TCT-BL), Alternate-Total Cross Tied-Honey Comb (A-TCT-HC) and Alternate-Bridge Link-Honey Comb (A-BL-HC) under uniform irradiance and various PSC. All the PV configurations are simulated in MATLAB/SIMULINK software and a 6 × 6 array of 7200 Wp is considered for investigation. The performance parameters considered for comparison are maximum output power, maximum output voltage, maximum output current, number of peaks, open circuit voltage, short circuit current, fill factor, shading loss, mismatching power loss and efficiency. Eight different shading patterns namely uneven row, uneven column, diagonal, central, long, and wide, random, L-shaped and triangular are considered for simulations. The performance analysis proves that the proposed A-TCT-BL PV configuration outperforms the conventional hybrid PV configuration in terms of enhanced output power and efficiency. It also significantly reduces the number of peaks and minimises mismatching losses under most of the PSC.

A maximum power point tracking technique based on bypass diode mechanism for PV arrays under partial shading