A modified particle swarm optimization algorithm to enhance MPPT in the PV array

Due to the growing demand for electrical power, the researchers are trying to fulfill this demand by considering different ways of renewable energy resource as existing energy resources failed to do so. The solar energy from the sun is freely available, and by using photovoltaic (PV) cell power can be generated. However, it depends on rays fall on the PV cell, climatic condition. Thus, to enhance the efficiency of the photovoltaic (PV) systems, maximum power point tracking (MPPT) of the solar arrays is needed.The output of solar arrays mainly depends on solar irradiance and temperature. The mismatch phenomenon takes place due to partial shade, and it causes to the power output, which brings the incorrect operation of traditional MPP tracker. In this shaded condition, PV array exhibits multiple extreme points. In general, under this scenario, the MPPT approaches fail to judge the MPP, and it leads to low efficiency. The conventional approaches of PSO based algorithms can able to track the MPP under shading condition. However, the optimization process leads to issues in tracking speed. Thus, there a need for an efficient MPPT system which can track MPPT effectively in shaded condition? Hence, the proposed manuscript presents a modified Particle Swarm Optimization (PSO) algorithm is introduced to enhance the tracking speed as well as performance. The outcomes of the proposed system are compared with the traditional PSO system and are found that the tracking speed of MPP, accuracy, and efficiency is improved

Artificial Intelligence and Bio-Inspired Soft Computing-Based Maximum Power Plant Tracking for a Solar Photovoltaic System under Non-Uniform Solar Irradiance Shading Conditions - A Review

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

Maximum power point tracking under partial shading conditions using an embedded system

The effects of global warming are deteriorating the planet and have enforced strict legıslatıons for carbon footprint reductıons. One of the main causes of global warming is the use of fossil fuels for power generatıon. Renewable energy is the solution to this problem as it produces electricity in a clean way. One of the promising forms of renewable energy is photovoltaic. However, solar is intermittent source of energy and dependent upon a number of factors including solar intensity and shadowing effects. This work aims to develop an effective and inexpensive microcontroller based control scheme to track the maximum power point in standalone solar photovoltaıc power systems. In conventional photovoltaic systems, the power curve has a single peak of power. There are many algorithms to track maximum power to maximise the efficiency of the photovoltaic system. However, when the photovoltaic is partially shaded, the output power can have multiple power peaks. A unique algorithm is derived to find the largest peak out of the many peaks. The entire power curve is scanned to find the maximum peak with respect to voltage, using a microcontroller. The largest peak is known as the global peak then presented to the output. The most commonly used algorithms; “perturb and observe” and “incremental conductance” were used. The scanning process is then repeated after a certain amount of time to maintain the global peak. The algorithm has achieved this with minimal loss of power. The algorithm scans and finds the global peak in 15 minutes of intervals, this process takes one second. Therefore, one second duration of power loss occurs from the photovoltaic in every 15 minutes. The algorithms are embedded in parallax microcontroller. Compare to the numerical Simulink model of photovoltaic systems experimental tracking efficiencies are slower. Nevertheless, in principle of the algorithms, perturb and observe works better than incremental conductance technique in terms of accuracy. The concentrated photovoltaic is required to move 11 times on an average day by using 0.7 W of power each time it moves, that of which the current photovoltaic modules can provide