70% decrease of hot-spotted photovoltaic modules output power loss using novel MPPT algorithm

The phenomenon of 'hot-spotting' within photovoltaic (PV) panels, where a mismatched cell/cells heats up, leads to reliability and efficiency issues. In this brief, a novel maximum power point tracking (MPPT) algorithm is developed to compensate for hot-spotted PV module effects, thus increasing the output power and improving reliability. The MPPT algorithm implements two mitigation processes; the first to identify the optimum power-voltage curve to track the global maximum power point (GMPP). The second process is to manipulate the output power toward the GMPP through the control of the perturbation step size. In order to verify the appropriateness of the proposed algorithm, multiple hot-spotted PV modules were tested under various environmental conditions. Significantly, the algorithm reduces the hot-spotted PV modules output power loss by at least 70% under all irradiance transition scenarios, slow, medium, and fast

Evaluasi PLTS off-grid 4 kWp ITN Malang di bawah kondisi partial shading dengan metode rekonfigurasi array PV untuk meningkatkan kinerja PLTS

Dalam sistem PV, setiap susunan terdiri dari banyak modul PV yang dihubungkan secara seri maupun paralel dengan tujuan untuk menghasilkan daya keluaran yang diinginkan. Kondisi bayangan parsial membuat sistem PV mengalami penurunan daya, sehingga mengakibatkan kemampuan pembangkitan daya tidak mencapai titik maksimum. Dan bayangan parsial ini adalah masalah serius pada suatu PLTS. Untuk meningkatkan hasil daya keluaran PLTS yang mengalami penurunan, maka dalam penelitian ini menyajikan analisis susunan PV dengan beberapa metode konfigurasi yang digunakan yaitu konfigurasi Series Parallel (SP), Honey Comb (HC), Bridge Link (BL), dan Total Cross Tie (TCT) dengan menggunakan software MATLAB. Disini diperoleh perbandingan konfigurasi yang memberi peningkatan daya yang lebih baik saat terjadi kondisi partial shading dari susunan modul PV konfigurasi awal. Penelitian ini dilakukan pada PLTS Off-Grid ITN Malang, dengan susunan PV 10 x 4 yang terhubung dengan dioda bypass. Hasil simulasi dari empat metode konfigurasi yang diusulkan, menunjukkan bahwa konfigurasi Total Cross Tie (TCT) menghasilkan peningkatan daya paling baik pada susunan modul PV di bawah kondisi partial shading. Peningkatan daya konfigurasi Total Cross Tie (TCT) sebesar 4,5 % untuk pagi hari dan 3,8 % untuk sore hari, terhadap konfigurasi Series Parallel sebagai Basecase dari penelitian ini

Design of a MPPT System Based on Modified Grey Wolf Optimization Algorithm in Photovoltaic System under Partially Shaded Condition

Conventional Maximum Potential Monitoring strategies such as perturbation and observation, incremental conduct, and climbing can effectively monitor the maximum power point in uniform shading, whereas failing in a partially shaded condition. Nevertheless, it is difficult to achieve optimal and reliable power by using photovoltaics. So, to solve this issue, this article proposes to monitor the photovoltaic system's global optimum powerpoint for partial shading with a Modified Gray Wolf Optimizer (MGWO) based maximum power point tracking algorithm. Under partial shadows, a mathematical model of the PV system is built with a single diode, EGWO is used to monitor global maximum power points.  A photovoltaic system includes deciding which converter is used to increase photovoltaic power generation. The MPPT architecture uses a modified gray wolf optimization algorithm to quickly track the output power and reduce photovoltaic oscillations. The efficiency of the maximum power tracker is better than the GWO algorithm of up to 0,4 s with the modified gray wolf optimization algorithm. Converters are used to resolve the power losses often occurring in PV systems with a soft-buck converter process.  The output of the power generator is greater than the soft-switching buck converter. The simulation and experimental results obtained suggest that both the P & O and IPSO MPPTs are superior to the proposed MPPT algorithm, the proposed algorithm increases the traceability efficiency. The suggested algorithm has the fastest follow-up speed since the α value decreases during the iteration exponentially

Rapid control prototyping based on 32-Bit ARM Cortex-M3 microcontroller for photovoltaic MPPT algorithms

Since the beginning of the war in Syria, most of the electricity infrastructure has been destroyed, leaving millions with unreliable energy. Syrians have encountered high electricity production costs and environmental damage costs resulting from the utilization of fossil fuels. Similarly, Syria has abundant solar energy can be exploited to meet its electrical power needs. However, because of a lack of expertise in solar energy conversion and the high cost of smart technology, Syrians have typically used photovoltaic systems in primitive ways, in which the efficiency of solar energy conversion is low. There is, therefore, a need for inexpensive, easy-to-implement, yet highly efficient and high performing solutions. Using the STMicroelectronics 32-bit ARM as a maximum power point tracking (MPPT) controller offers a potential solution to the problem of low conversion efficiency in standalone solar systems. In this study, using Matlab-Simulink and STMicrelectronics-32 bit ARM board, simulation and practical test is set up to evaluate the performance of the Perturbation & Observation, Incremental Conductance and Fuzzy Logic MPPT algorithms, in order to determine the most appropriate algorithm to use in small scale solar energy systems. Therefore, one main objective of this study is to explore rapid control prototyping tools for saving time and effort to the experts in the implementation process of the proposed systems. The results indicate the effectiveness of Fuzzy logic algorithm to draw more energy, decrease oscillation and provide a fast response under variable weather conditions. Furthermore, the three algorithms were able to find and track MPP

Adapted flower pollination algorithm for a standalone solar photovoltaic system

This Extraction of the maximum electrical power from a solar photovoltaic (PV) system under numerous weather conditions is required to reduce its payback time period, per unit energy price, and to compensate for the high initial price of the solar PV system. This could only be achieved by continuously operating the solar PV system at its maximum power point (MPP) under several weather conditions. Unlike under uniform weather conditions (UWC), identification of the real MPP (Global MPP) under partial shading condition (PSC) in a reasonable time is a challenging task due to the formation of multiple local MPP in the power-voltage (P-V) characteristic curve of a solar PV array. The nature-inspired MPP tracking algorithms have been proved suitable for global MPP tracking (MPPT) under PSC. In this research paper, a renowned nature-inspired flower pollination algorithm (FPA) is deeply reviewed, modified, and integrated with the random walk filter to improve its performance in terms of tracking speed, and efficiency. A comparison of the proposed ‘Adaptive Flower Pollination Algorithm (AFPA)’ and conventional FPA algorithm has been made under zero, weak, and strong PSCs for a 4S solar PV array. The proposed algorithm has produced remarkable results in tracking speed, and efficiency, for the global MPP (GMPP) tracking under different PSCs. The simulation is performed in MATLAB/Simulink software

Maximum power point tracking based on improved spotted hyena optimizer for solar photovoltaic

The conventional maximum power point tracking (MPPT) method such as perturb and observe (P&O) under partial shading conditions with non-uniform irradiation, can get trapped on local maximum power point (LMPP) and cannot reach global maximum power point (GMPP). This study proposes a bio-inspired metaheuristic algorithm spotted hyena optimizer (SHO) and improved SHO as a new MPPT technique. The proposed SHO-MPPT and improved SHO-MPPT are used to extract GMPP from solar photovoltaic (PV) arrays operated under uniform irradiation and non-uniform irradiation. Simulation with Powersim (PSIM) and experimental with the emulated PV source were presented. Furthermore, to evaluate the performance of the proposed algorithm, SHO-MPPT is compared with P&O-MPPT and particle swarm optimization (PSO)-MPPT. The SHO-MPPT has an accuracy of 99% and has the good capability, but there are power fluctuations before reaching MPP. Therefore, improved SHO-MPPT was developed to get better results. The improved SHO-MPPT proved high accuracy of 99% and faster than SHO-MPPT and PSO-MPPT in tracking the maximum power point (MPP). Furthermore, there are minor power fluctuations