New maximum power point tracking technique of a grid-connected PV system with subtractive clustering

摘要

With great increasing concerns about fossil fuel shortage, global warming, and damage to the environmental system, the encouraging to increase in the alternative energy resources which have low operation cost and low pollutant emissions have a great concern. The photovoltaic (PV) system is one of the renewable energy resources widely spread in the energy market in the globe as well as Egypt. Several natural conditions affect the output power of the PV system such as solar irradiance and ambient temperature. Maximum Power Point Tracking (MPPT) techniques for controlling DC-DC boost converter tend to reach for the maximum output power. Various MPPT based techniques have been designated in the literature. In this paper, the Adaptive Neuro-Fuzzy Inference System technique based on Subtractive Clustering method is proposed and compared with other previously used techniques. A grid-connected PV system of 100kW is considered and investigated. From results, the system response with the proposed technique for MPPT is faster, robust, and more stable than other techniques. In addition, there are no any overshoots in the DC link voltage and the value of AC output power is increased the obtained results are promising.