Implementation of Natural-inspired Algorithms and Topology Strategy on Maximum Power Point Tracking for High Concentration Photovoltaic System under Partial Shading Conditions

• Main Authors: CHEN, XIANG, 陳祥
• Other Authors: HUANG, YU-PEI
• Format: Others
• Language: zh-TW
• Published: 2018
• Online Access: http://ndltd.ncl.edu.tw/handle/hq4q84

碩士 === 國立金門大學 === 電子工程學系碩士班 === 106 === In this study, two techniques "software algorithm" and "hardware reconfiguration circuit" were separately proposed to improve the power output of high concentration photovoltaic (HCPV) systems under partial shading conditions (PSC). The maximum power point (MPP) of an HCPV system varies rapidly under changing environmental conditions. Therefore, a "software algorithm" maximum power point tracking (MPPT) with rapid response is needed. However, the power-voltage (P-V) curve of a solar system under PSC exhibits multi-peaks of each interval. As a result, although the tracking speed of conventional MPPT algorithms is rapid, they usually couldn’t accurately track the global maximum power point (GMPP) under PSC. To overcome this issue, researchers have proposed using various natural-inspired algorithms for MPPT, such as genetic algorithm (GA) etc. Although GA could accurately track GMPP under PSC, it has complicated calculation and slow tracking speed. In order to further improve the tracking speed of GA with non-decreasing accuracy, a novel modified genetic algorithm (MGA) is proposed in this study. The proposed MGA integrates the calculation processes of conventional firefly algorithm (FA) and difference evolution (DE) algorithm for MPPT of HCPV systems under PSC. In the second part of this thesis, the strategy of using "hardware reconfiguration circuit" to improve total output power of an HCPV system is studied. Conventional reconfiguration circuit methods rearrange serial and parallel connections of a solar array under PSC which could increase the total output power of the system. However, they need complicated switching control algorithms and large number of switches and sensors. In order to improve this strategy and overcome its disadvantages, a novel modified circuit reconfiguration (MCR) method is proposed in this research. The total-cross-tied (TCT) topology is adopted in the MCR to simplify its switching control algorithm and reduce the number of switches and sensors. The performance of the two proposed techniques were first simulated and then evaluated by practical hardware. In the first phase, an HCPV circuit model and various PSC patterns with different solar radiance were established using the M-file and Simulink toolbox of Matlab software for preliminary simulation and parameters fine tuning. In this second phase, the hardware evaluation experiments of the proposed MGA were conducted using a solar I-V curve simulator, while actual LED light sources and HCPV modules were adopted for MCR evaluation. Evaluation results demonstrate that when compared with conventional GA, the execution time and tracking accuracy of the proposed MGA could improve around 69.4% and 4.16%, respectively. In addition, when compared with conventional FA, the execution time and tracking accuracy could improve around 42.9% and 1.85%, respectively. On the other hand, when compared with conventional series-connection and TCT methods, the total output power of an HCPV system using the proposed MCR method could increase around 29.12% and 40.11%, respectively. The advantage of the proposed MGA is fast tracking speed with high accuracy, while the MCR method can successfully effectively increase output power with simplified control algorithm and reduced hardware cost. Both methods can be implemented not only to HCPV systems but also different solar systems. In addition, the proposed prototype architecture is capable of being extended to larger scale solar arrays.