Optimal Design of Grid-connected Photovoltaic (PV) Power Plants using Optimisation Algorithms


Thesis Type: Doctorate

Institution Of The Thesis: Universiti Malaysia Perlis, School of Electrical System Engineering, Electrical System Engineering, Malaysia

Approval Date: 2021

Thesis Language: English

Student: Tekai Eddine Khalil Zidane

Principal Supervisor (For Co-Supervisor Theses): Mohd Rafi Bin Adzman

Co-Supervisor: Mohammad Faridun Naim Tajuddin, Ali Durusu, Samila Mat Zali

Abstract:

The increasing demand for electricity is leading to an increase of the production capacity by using different resources. In this context, renewable energy such as PV systems and Wind power are growing rapidly to respond to the high demand of energy. In this sense, the solar PV technology is most installed as of the end of 2017 followed by wind power. Currently, available design methods did not simultaneously take into account all design characteristics of large PV plants, such as the effect of the mutual shading between two rows which reduce the PV plant produced power, but also the arrangement of the PV modules. These parameters are highly affecting the energy production and the capital as well as the lifetime maintenance costs. The present work was initiated to introduce the new method to design large-scale PV power plants that can reduce the annual energy cost as well as the installation site cost, also to minimize the size of the PV plant area taking into account the shape of the PV plant field as well as maximizing the total energy production during the PV plant operational lifetime and to minimize the Levelized Cost of Energy (LCOE). The elementary main of this research is using evolutionary algorithms optimization for designing large-scale photovoltaic power plants. The construction of the new method is the combination of all the parameters of components that exist in the installation site and meteorological data of the location. The validation of the alternatives and parameters of case of studies and results will be done through the comparison of an existing power plant and this improved methodology also using PVSYST software.