Application Of Adaptive Weight Variation Cat Swarm Algorithm In MPPT Control Of Photovoltaic System

The maximum power point tracking technology is the key technology of the photo voltaic power generation system. It is controlled by a control algorithm to control the output voltage and load voltage of the phot ovoltaic cell to match, so that the photovoltaic power generation system always works at the maximum power point, th us ensuring the pow er generation system output power maximum. Currently commonly used MPPT technology are: constant volt a ge method,conductance incremental method, disturbance observation method and fuzzy control method. In the practical application, due to the co mplexity of the environment PV arrays are often in the loc al shade or uneven light intensity of the situation, resulting in the PV array output PU characteristic curve presents a multi-peak phenomenon, the traditional single-peak o ptimization based on th e control method in this case can not effectively track the maximum power point.Considering the cat algorithm has good performance in multimodal function optimization and global optimization, this paper applies the cat algorith m to the maximum power point tracking of photovoltaic power generation system, and proposes an adaptive weight variation cat algorithm to photovoltaic. Battery series as the research object solves the problem of multi-peak optimization under local shading.In this paper, the commonly used mathematical model is built by MATLAB / Slmulink, and the output characteristic curve of the photovoltaic cell is simulated by changing the light intensity and temperature. The output characteristics of the photovoltaic cell are simulated and simulated in the case of lo cal shading. Which provides the theoretical basis for the research of MPPT algorithm. This paper analyzes the principle of the maximum power point tracking of PV system and analyzes the basic re alization process of the commonly used maximum power point tracking algorithm. It summarizes the advantages and disa dvantages of these algorithms and makes careful study on the basic cat algorith m implementation process.And it comes up with adaptive weight variation cats algorith m which anal yzes the ad aptive weighting and m utation operator in the algorithm in detail and describes the im plementation process of adaptive w eight variation cat algorithm in simulating local maximum shading of PV syste m . In the MATLAB / Si mulink environment, the simulation model is simulated and compared with the basic cat algorithm and the conductance increment method in the same environment. The feasibility of the improved algorithm and the tracking of the algorithm are evidenced. Fast and high precision.