Comparative Analysis of Bio-Inspired Maximum Power Point Tracking Algorithms for Solar Photovoltaic Applications
Keywords:
Maximum Power Point Tracking, Solar Photovoltaic System, Partial Shading, BI-based MPPTAbstract
Research and development in Maximum Power Point Tracking in solar photovoltaic systems gains more importance in the modern world. The main issues and challenges in solar photovoltaic systems are partial shading conditions, rapid variations in atmospheric conditions, installation cost, cost of semiconductor material, and poor solar panel power conversion efficiency. More research and development is taking place in Maximum Power Point Tracking to overcome those issues in solar photovoltaic systems. However, most MPPT technics cannot reach their optimum performance to operate PV panels at their maximum available power. To overcome this issue, research is focused on the advanced Maximum Power Point Tracking algorithm and hybrid MPPT algorithm rather than conventional MPPT algorithms. In this research, the advanced MPPT, such as bio-inspired Maximum Power Point Tracking methods, are evaluated based on the speed of convergence, requirements of sensors, robustness and efficiency, tracking efficiency, and tracking accuracy. The comparative results show that the ABC algorithm performs best among other bio-inspired MPPT algorithms in fast-changing atmospheric conditions. In addition, the scope and review of hybrid MPPT in a solar photovoltaic system are discussed in brief.
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