Application of bio-inspired algorithms in maximum power point tracking for PV systems under partial shading conditions - A review

作者：Li, Guiqiang^*; Jin, Yi^*; Akram, M. W.; Chen, Xiao; Ji, Jie

来源：RENEWABLE & SUSTAINABLE ENERGY REVIEWS, PERGAMON-ELSEVIER SCIENCE LTD, THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND, 840-873, 2018-01.

DOI：10.1016/j.rser.2017.08.034

• Photovoltaic (PV) system
• Maximum power point tracking
• Bio-inspired algorithm
• Partial shading situations
• Global maximum power point tracking

Solar energy is one of the most promising renewable energy resource due to its variety of advantages. The photovoltaic systems have a remarkable development over the past few decades. As the maximum power point of the photovoltaic system varies with the change in environmental conditions, the maximum power point tracking technology is necessary to harvest maximum power from the photovoltaic systems. However, multiple peaks occur in the power-voltage (P-V) curve during partial shading conditions. In such condition, many traditional maximum power point tracking methods like perturbation and observation, and incremental conductance may become invalid due to involvement in the local maximum power point. Many advanced methods based on the artificial intelligence like artificial neural network, and fuzzy logic control can track the global maximum power point. However, they are not feasible in real complex environment because they need massive training and broader experience. Alternatively, bio-inspired maximum power point tracking algorithms deal properly with such situations. In recent years, researchers have widely applied bio-inspired algorithms to track the global maximum power point of photovoltaic system during partial shading situations. This paper presents a comprehensive review of the bio-inspired algorithms used for global maximum power point tracking. Various tracking methods are discussed and compared in terms of their characteristics and corresponding improved methods. It also presents the advantages and disadvantages of each method. The modified and combined forms of these methods found to have better performance than original algorithms. Overall, the performance of swarm intelligence based algorithms is found better than evolutionary algorithms. This review may help the researchers to acquire comprehensive information about the application of bio-inspired algorithms to gain maximum power from the photovoltaic systems, and furthermore, help them to choose an efficient way of global maximum power point tracking in photovoltaic systems during partial shading conditions.

• 出版日期2018-1
• 单位中国科学技术大学; 火灾科学国家重点实验室