Control of Hybrid Renewable Energy Systems Using AI Techniques

Zusatztext

This work, presents the development and control of a hybrid renewable energy system connected to the grid. The investigated system includes a photovoltaic (PV) panels, permanent magnet synchronous generator based wind turbine, and a battery as an energy storage system. PV system with maximum power point tracking based Cuckoo Search (CS) algorithm is developed. CS provides several advantages such as the process of tuning parameters is few with high efficiency beside fast convergence. Cuckoo search uses a random walk according to levy flight in searching process. Maximum Power Point Tracking (MPPT) by using cuckoo search is compared with other two methods, neural network method, which needs training for data, and the incremental conductance method. DC / DC converter is used with direct duty cycle control of PWM based PID controller. The PID controller parameters are tuned by using Particle Swarm Optimization (PSO).

Autorenportrait

M. Osama Abed El-Raouf earned his BSc of Electrical Power Engineering at Shoubra Faculty of Engineering, Benha University, 2013. he earned his MSc at Shoubra Faculty of Engineering, Benha University, 2016. he is a Researcher Assistant in the Building Physics and Environmental Research Institute, Housing, and Building National Research, Egypt.

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