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Modeling, Analysis, and Control of Wide Distributed Large-Scale PV Power Plant Using Recent Optimization Techniques
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Author(s): Rania Gamal Mohamed (Marg High Institute for Engineering and Modern Technology, Cairo, Egypt)and Mohamed Ahmed Ebrahim (Faculty of Engineering at Shoubra, Benha University, Egypt)
Copyright: 2021
Pages: 21
Source title:
Handbook of Research on Modeling, Analysis, and Control of Complex Systems
Source Author(s)/Editor(s): Ahmad Taher Azar (Faculty of Computers and Artificial Intelligence, Benha University, Benha, Egypt & College of Computer and Information Sciences, Prince Sultan University, Riyadh, Saudi Arabia)and Nashwa Ahmad Kamal (Faculty of Engineering, Cairo University, Giza, Egypt)
DOI: 10.4018/978-1-7998-5788-4.ch019
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Abstract
Atom search optimization algorithm (ASOA) has recently been explored to develop a novel algorithm for distributed optimization and control. This chapter proposes the ASOA-based design of maximum power point tracking controllers (MPPTCs) for controlling the boost converter voltage to harvest the maximum power and enhance the damping of oscillations in the output power of the photovoltaic power plants. The proposed ASOA-based MPPTCs are PI and fractional-order PI controllers. ASOA is utilized to search for optimal controller parameters by minimizing a candidate time-domain based objective function. The performance of the proposed ASOA-based MPPTCs has been compared to the MPPTCs optimized by grey wolf optimizer (GWO) to demonstrate the superior efficiency of the ASOA-based MPPTCs. Simulation results emphasis on the better performance of the proposed MPPTCs compared to MPPTCs and GWO-based PI- FOPI controllers over a wide range of operating conditions.
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