Hybrid SCA and adaptive controller to enhance the performance of grid-connected PV system

Abstract

Future of generation depends on the renewable energy resources due to lack of fuel and the problems of emissions. Photovoltaic (PV) system is a promising type of renewable energy resources. Non uniformity of irradiance, temperature variation, and partial shading conditions are the main disturbances associated with PV systems. Most of literatures focus on enhancing the PV performance and to achieve Maximum Power Point Tracing (MPPT) based on offline Optimization techniques. These techniques suffer from complicated mathematical burden, long computing time, and should be repeated for any change in the operating conditions/system parameters. This paper proposed a hybrid adaptive controller to improve the system performances under several disturbances, as well as to stabilize the operation of the MPPT. Thus, the proposed controller affords tight and accurate MPPT. The gains of the proposed controller are updated automatically with the variation in the operating conditions. The initialization of the proposed a hybrid adaptive controller is carried out utilizing the Sine-Cosine Algorithm (SCA). Finally, the proposed system is evaluated through comparison with one of the newly presented techniques that achieve accurate MPPT.