Title: Artificial Intelligence Application for Photovoltaic Systems

Biography:

Hany M. Hasanien (M 09, SM 11) received his B.Sc., M.Sc. and Ph.D. degrees in Electrical Engineering from Ain Shams University, Faculty of Engineering, Cairo, Egypt, in 1999, 2004, and 2007, respectively. From 2008 to 2011, he was a Joint Researcher with Kitami Institute of Technology, Kitami, Japan. From 2012 to 2015, he was Associate Professor at College of Engineering, King Saud University, Riyadh, Saudi Arabia. Currently, he is Professor at the Electrical Power and Machines Department, Faculty of Engineering, Ain Shams University. His research interests include modern control techniques, power systems dynamics and control, energy storage systems, renewable energy systems, and smart grid. Prof. Hasanien is an Editorial Board Member of Electric Power Components and Systems Journal. He is Subject Editor of IET Renewable Power Generation, Frontiers in Energy Research and Electronics MDPI. He has authored, co-authored, and edited three books in the field of electric machines and renewable energy. He has published more than 200 papers in international journals and conferences. His biography has been included in Marquis Who’s Who in the world for its 28 edition, 2011. He was awarded the Encouraging Egypt Award for Engineering Sciences in 2012. He was awarded Institutions Egypt Award for Invention and Innovation of Renewable Energy Systems Development in 2014. He was awarded the Superiority Egypt Award for Engineering Sciences in 2019. Currently, he is IEEE PES Egypt Chapter Chair and is Editor in Chief of Ain Shams Engineering Journal.   

Abstract

Photovoltaic (PV) systems represents the second item of the renewable energy installation after the wind systems. Several investments are oriented to the PV industry where there is a deep reduction of components cost. This lecture presents the application of metaheuristic algorithms used to estimate the unknown parameters of the three-diode PV model of such PV panels. The principal goal of the study is to achieve an accurate PV model that can be applied to different systems. The accuracy of the PV model affects the accuracy of dynamic analyses of the system. The PV modeling is considered as an optimization problem, which represents the root mean squared current error between the calculated model current and the experimental current of the PV panel. Different metaheuristic algorithms can be applied to solve the optimization problem and obtain the unknown parameters of the PV model. The effectiveness of the proposed PV model is validated by several numerical results, which are carried out under different environmental conditions. The simulation results are compared with the experimental results for different PV panels. With the incorporation of metaheuristic algorithms, an accurate PV model of any PV panel is built. The application of these algorithms and artificial intelligence is very powerful in this research area.