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논문 기본 정보

자료유형
학술저널
저자정보
Ji-Ying Shi (Tianjin University) Fei Xue (State Grid Ningxia Electric Power Company) Le-Tao Ling (Tianjin University) Xiao-Fei Li (State Grid Electric Power Research Institute) Zi-Jian Qin (Tianjin University) Ya-Jing Li (Tianjin University) Ting Yang (Tianjin University)
저널정보
전력전자학회 JOURNAL OF POWER ELECTRONICS JOURNAL OF POWER ELECTRONICS Vol.17 No.2
발행연도
2017.3
수록면
476 - 489 (14page)

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Under partial shading conditions (PSCs), multiple maximums may be exhibited on the P-U curve of string inverter photovoltaic (PV) systems. Under such conditions, heuristic methods are invalid for extracting a global maximum power point (GMPP); intelligent algorithms are time-consuming; and model-based methods are complex and costly. To overcome these shortcomings, a novel hybrid MPPT (MPF-IP&O) based on a model-based peak forecasting (MPF) method and an improved perturbation and observation (IP&O) method is proposed. The MPF considers the influence of temperature and does not require solar radiation measurements. In addition, it can forecast all of the peak values of the PV string without complex computation under PSCs, and it can determine the candidate GMPP after a comparison. Hence, the MPF narrows the searching range tremendously and accelerates the convergence to the GMPP. Additionally, the IP&O with a successive approximation strategy searches for the real GMPP in the neighborhood of the candidate one, which can significantly enhance the tracking efficiency. Finally, simulation and experiment results show that the proposed method has a higher tracking speed and accuracy than the perturbation and observation (P&O) and particle swarm optimization (PSO) methods under PSCs.

목차

Abstract
I. INTRODUCTION
II. THEORETICAL MODEL OF A PV CELL
III. MODEL-BASED PEAK FORECASTING METHOD
IV. SIMULATION RESULTS AND ANALYSIS
V. EXPERIMENT RESULTS AND ANALYSIS
VI. CONCLUSION
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UCI(KEPA) : I410-ECN-0101-2017-560-002321319