Conventional Techniques for Maximum Power Point Tracking

This paper reviews the existing models, connection schemes and maximum power point tracking (MPPT) methods of PV arrays. The partial shading causes significant power losses. It is very difficult to maintain uniform irradiance over the entire PV array, especially for rooftop or building-integrated PV systems. The aspects such as connection scheme of PV array, shading pattern and maximum power point tracking (MPPT) techniques, etc., decide the power generated by the PV array. The conventional MPPT methods are only capable of reaching maximum power point (MPP) in identical insolation situations. Hence, conventional MPP tracking becomes inept due to the existence of several peaks in the P-V characteristics. There are different global maximum power point (GMPP) tracking techniques available in the literature that operate in partial shading scenarios. The reconfiguration of the PV array reduces the number of multiple peaks. This reduction in several peaks makes conventional MPP tracking techniques competent even under partial shading conditions with low implementation complexity and higher tracking speed. This paper can assist scientists in choosing a precise objective-based PV module model, connection schemes and MPP tracking methods out of numerous schemes available in the literature.

To mitigate problems like energy shortage and environmental degradation caused by conventional energy sources, it needs to shift from conventional energy to non-conventional energy sources. The solar photovoltaic (PV) technology emerges as one of the leading non-conventional energy sources. To operate a PV system at its maximum efficiency, it requires the operating module at maximum power output point (MPP). There are many conventional as well as advanced maximum power point tracking (MPPT) techniques developed and implemented for a solar PV system. This work provides a comparative analysis of the conventional and fuzzy logic controller (FLC)-based MPPT techniques for a solar PV system. In this study, performance of two conventional techniques is considered, i.e., perturb and observe (P & O) and incremental conductance (IC) MPPT technique. The analysis of the PV system is performed for different solar irradiance levels. The comparative study is evaluated for complexity, tracking time, efficiency, range of power, voltage, and current oscillations. The DC-DC boost converter is used for operation of the proposed PV system at MPP. The implementation of the entire system and control algorithms has been modeled in MATLAB Simulink.

This paper presents a novel Simulink models with an evaluation study of more widely used On-Line Maximum Power Point tracking (MPPT) techniques for Photo-Voltaic based Battery Storage Systems (PV-BSS). To have a full comparative study in terms of the dynamic response, battery state of charge (SOC), and oscillations around the Maximum Power Point (MPP) of the PV-BSS to variations in climate conditions, these techniques are simulated in Matlab/Simulink. The introduced methodologies are classified into two types; the first type is conventional hill-climbing techniques which are based on instantaneous PV data measurements such as Perturb & Observe and Incremental Conductance techniques. The second type is a novel proposed methodology is based on using solar irradiance and cell temperature measurements with pre- build Adaptive Neuro-Fuzzy Inference System (ANFIS) model to predict DC–DC converter optimum duty cycle to track MPP. Then evaluation study is introduced for conventional and proposed On-Line MPPT techniques. This comparative study can be useful in specifying the appropriateness of the MPPT techniques for PV-BSS. Also the introduced model can be used as a valued reference model for future research related to Soft Computing (SC) MPPT techniques. A significant improvement of SOC is achieved by the proposed model and methodology with high accuracy and lower oscillations.

In this work, a simulation study and comparative analysis of conventional Maximum Power Point Tracking (MPPT) technique, i.e., Incremental Conductance (IC) with nonlinear technique, i.e., Ripple Correlation Control (RCC), has been done. Photovoltaic (PV) array and the DC/DC boost converter along with MPPT control strategy have been implemented and simulations analysis has been presented for both the techniques for various solar irradiance levels at 25 °C temperature. The system has been designed to achieve 450 V and 10 kW output at 1000 W/m2 irradiation, which is attained through a DC/DC boost converter. Simulation results show that the IC technique’s output is very much affected by oscillations under steady-state and varying environmental conditions, which affects the system’s stability; whereas, RCC removes all ripples from voltage, current, and power outputs in steady-state and upto some extent in transient state, due to its inherent ripple removal feature. However, during transitions RCC also exhibits underdamped response, but it is minimum as compared to other MPPT techniques.KeywordsPhotovoltaic (PV)DC/DC Boost converterMaximum Power Point Tracking (MPPT)IrradianceRipplesIncremental Conductance (IC)Ripple Correlation Control (RCC)

Substantial progress in solar photovoltaic (SPV) dissemination in grid-connected and standalone power generation systems has been witnessed during the last two decades. However, weather intermittency has a non-linear characteristic impact on solar photovoltaic output, which can cause considerable loss in the system’s overall output. To overcome these inevitable losses and optimize the SPV output, maximum power point tracking (MPPT) is mounted in the middle of the power electronics converters and SPV to achieve the maximum output with better precision from the SPV system under intermittent weather conditions. As MPPT is considered an essential part of the SPV system, up to now, many researchers have developed numerous MPPT techniques, each with unique features. A Google Scholar survey from 2015–2021 was performed to scrutinize the number of published review papers in this area. An online search established that on different MPPT techniques, overall, 100 review articles were published; out of these 100, seven reviews on conventional MPPT techniques under shading or partial shading and only four under non-uniform solar irradiance are published. Unfortunately, no dedicated review article has explicitly focused on soft computing MPPT (SC-MPPT) techniques. Therefore, a comprehensive review of articles on SC-MPPT techniques is desirable, in which almost all the familiar SC-MPPT techniques have to be summarized in one piece. This review article concentrates explicitly on soft computing-based MPPT techniques under non-uniform irradiance conditions along with their operating principles, block/flow diagram. It will not only be helpful for academics and researchers to provide a future direction in SC-MPPT optimization research, but also help the field engineers to select the appropriate SC-MPPT for SPV according to system design and environmental conditions.

Solar photovoltaic (PV) system contributes a significant role in meeting power requirements and helps the decentralization of power generation and distribution. The output of the individual photovoltaic module depends on local temperature and irradiance. Since the variation of these parameters depends on the environmental factors, it is difficult to obtain maximum power in all instances. The maximum power point tracking (MPPT) technique is used for tracking the maximum power available at a particular instant. This paper presents the maximum power extraction from a photovoltaic system using Artificial Intelligence (AI) techniques. AI based methods provide a fast dynamic response with high accuracy and mitigate the effects of partial shading. A comparative study is performed for various AI based MPPT techniques such as Fuzzy, Artificial Neural Network (ANN), and Adaptive Neuro Fuzzy Inference System (ANFIS). PV module output is interfaced with the resistive load through the Z-Source inverter (ZSI). The ZSI boost the input voltage and provides an AC output voltage. The AI based MPPT techniques have been investigated with conventional Z-source Inverter (ZSI) and Switched Inductor Z-Source inverter (SL-ZSI). A simple boost control technique is employed to control, both conventional and SL Z-source inverter. The performance of the system is verified using MATLAB Simulink.

Renewable energy source (RES) production has increased nowadays due to the depletion of fossil fuel reserves and the rise in greenhouse emissions. Incorporating RES into the grid may produce additional problems in power quality, system stability, harmonics and reliability owing to their sporadic nature. The RES is capable of operating in both ON and OFF electrical grid modes since ON-grid power systems are linked to the utility grid, while off-grid systems are not. However, because of the environmental variability, it can be challenging to obtain optimal voltage and extract maximum RES power. It is crucial to derive an optimal solution to obtain the maximum power from RES. Therefore, this paper proposes a bat algorithm for tracking (BAT) with a quantum neural network (QNN) for extracting maximum power from a PV panel. The Bat Optimization Algorithm (BOA) is used to select optimal parameters for QNN. The suggested method is designed via MATLAB/Simulink, and various parameters are considered, in which total harmonic distortion (THD) and efficiency analysis of the proposed method with an ant lion optimized cuckoo search (ALO-CS) algorithm are compared. Simulation and hardware implementation results demonstrate superior performance compared to the ALO-CS method. The proposed approach achieves a peak efficiency of 93.6% in simulation and 93.4% in hardware, with convergence times of 0.1[Formula: see text]s and 0.16[Formula: see text]s, respectively. Harmonic distortion is significantly reduced, with THD values of 0.43% in simulation and 0.7% in hardware using a current control technique. These results confirm that the QNN-BOA method provides faster tracking, higher efficiency and better power quality than conventional maximum power point tracking (MPPT) techniques, making it highly suitable for hybrid RES applications.

Recently, many Maximum power point tracking (MPPT) techniques are proposed in the Photovoltaic (PV) systems. However, a comprehensive comparison of various MPPT techniques especially the dynamic tracking performance has not been made quantitatively for different working conditions. By reviewing different methods, the day-by-day operating evaluation method with practical meteorological data is used in this paper. Furthermore, three typical MPPT techniques including fixed step size P&O method, variable step size incremental conductance method, and hybrid step size Beta method, are selected in the performance evaluation. In order to improve the experimental repeatability and minimize the effect of random environmental factor such as partial shading, an indoor test system that consists of a DC-DC boost converter, a PV emulator and a dSPACE is used. The practical meteorological data are used for the evaluation these typical MPPT techniques and main experimental results are presented.

In the last decade, there has been a substantial surge in the advancement of research into the maximum power point tracking (MPPT) controller. The MPPT approaches, on the other hand, continue to be in high demand due to the ease and simplicity with which tracking techniques can be implemented on the maximum power point (MPP). Diverse MPPT approaches and their modifications from various literature are categorized and thoroughly explored in this work, which is divided into two sections. The discussions are centered on the primary goal of attaining the most extraordinary feasible MPPT technique that produces the best results at the lowest possible expense. In order to determine which MPPT approaches to use, evaluations from earlier literature are used to guide the decision. In this section, we will examine the evaluation of the MPPT technique in two sections. Previously, in Part I, we explored the MPPT techniques based on constant parameters and trial-and- error. Part II of this article will examine the MPPT technique, which is based on mathematical computation, measurement, and comparison, and the algorithm development that has occurred in recent years. Furthermore, this section’s assessment for selecting MPPT approaches is based on previous literature reviews. To aid with this selection, the following criteria for the MPPT approach are proposed: sensors and analog/digital requirements, costeffectiveness, simplicity, stability, efficiency, and tracking speed. This enables the reader to select the MPPT technique that is most appropriate for their application.

Maximum power point tracking (MPPT) techniques work to track the maximum power from the PV cell. A lot of conventional MPPT techniques, such as the perturb and observe (P&O), succeed in catch the maximum power point (MPP) with a good performance. However, they suffer many problems during fast varying weather conditions, where slow time response and high oscillations are dominant. Also, it is difficult to select the right direction for new steps. This article illustrates two new P&O MPPT techniques for PV generation systems. They operate on the power-voltage (P-V) curve under different weather conditions. The first is an adaptive perturb and observe (A-PO) technique, which changes the perturbation step-size adeptly to deal with the rapidly varying weather conditions. The second is a hybrid perturb and observe technique (H-PO), which uses a variable step-size according to the location of the operating point relative to the MPP. The MATLAB/SIMULINK software is used to study the truth of the proposed techniques. The results demonstrate that both techniques attain the MPP faster than the conventional techniques and at a reduced oscillation rate.

In renewable system control engineering, Maximum Power Point Tracking (MPPT) techniques are considered as one of the key steps in photovoltaic (PV) system development. Indeed, some MPPT techniques provide high performance under uniform irradiation and temperature conditions. However, their performance significantly degrades when the two preceding climatic conditions suddenly change. Therefore, this paper proposes a new voltage regulation based on Fuzzy Logic Control (FLC) strategy and small-signal model of DC–DC booster converter. The proposed control scheme is mainly based on the indirect incremental conductance (Inc) technique, equipped with an optimal integrator controller (OIC). It is implemented in a PV system, consisting of a DC–DC boost converter connected to a resistive load, with the main objective of ensuring a good MPP tracking behavior for variable operating conditions. To achieve this objective, the proposed MPPT strategy is designed around two stages. First, the smooth reference voltage is ensured by a Single-Input Single-Output (SISO) fuzzy logic controller using the Inc technique based on the MPPT approach. Then, the optimal integrator controller stabilizing the closed-loop system is integrated with optimization of its parameter according to Routh’s criterion for resistive load variations. Simulation results confirm the effectiveness of the proposed MPPT technique compared to some commonly used MPPT approaches. The superiority of the proposal is proven by using efficiency ratio, which rises more than 98% in all case studies. These objectives are ensured for both uniform and critical sudden change in weather conditions, regardless of resistive load variations.

This paper focuses on the intelligent techniques used for tracking the maximum power point of the solar photovoltaic (SPV) system for varying environmental conditions. The most widely used perturb and observe (P&O) maximum power point tracking (MPPT) technique is discussed briefly for the comparison with the intelligent techniques. The paper proposes control technique for the SPV system by using fuzzy logic controller (FLC)-based MPPT algorithm and the optimisation of its various parameters by genetic algorithm (GA). The performance of the FLC optimised with GA is compared with the P&O and the fuzzy-based MPPT technique. MATLAB/simulink software is used to design the different stages of the MPPT controllers. Simulation results reported that GA optimised FLC perform much better than the P&O and fuzzy logic-based MPPT controllers.

A hybrid maximum power point tracking for partially shaded photovoltaic systems in the tropics

Maximum power point tracking (MPPT) techniques had evolved rapidly in the last decade with the evolution of power electronics. This paper presents a control technique for a variable speed, grid connected direct driven permanent magnet synchronous generator (PMSG). The PMSG is connected to the grid through three-phase diode rectifier followed by a boost converter controlled with the MPPT technique to maintain a constant DC bus voltage for different wind velocities. The paper compares between two MPPT techniques, HCS and fuzzy logic. The control depends upon sensorless rotor speed estimator through measuring the input dc voltage and current for the boost converter. The system performance is investigated using a MATLAB/ SIMULINK model for 2 MW PMSG wind turbine.

Photovoltaic (PV) systems are gradually becoming the key renewable source of electrical energy. But the nonlinear characteristics of the PV module require special techniques to harvest maximum power. The techniques used to track the Maximum Power Point (MPP) from the nonlinear I-V characteristics through power electronic circuits are known as Maximum Power Point Tracking (MPPT) techniques. Although enormous MPPT techniques have been anticipated in literature, each endures its own advantages and disadvantages. This paper proposes a novel hybrid technique to enhance the performance of Incremental conductance (InC) technique. Our proposed technique removes the limitations of InC under rapid changing environmental condition. It improves the efficiency and reduces the oscillation power loss under steady state. A hybrid combination of variable-step sized Incremental Conductance with Fractional Short Circuit Current (FSCC) technique is proposed in this research work. Initially, the FSCC forces the PV system to work near MPP and then InC technique track the exact peak. Matlab/Simulink software is used to implement the proposed hybrid technique. Finally, the results verify its superior performance under rapidly changing environmental conditions.