Optimal Allocation of Photovoltaic (PV) System Considering Weather Conditions using Evolutionary Programming (EP) for Enhanced Power System Resiliency

Abstract

This project introduces an optimal PV system allocation by considering weather conditions through a system reliability assessment. The Markov model is performed with embedded data of the PV generator and weather conditions to obtain a forced outage rate (FOR) and both (FOR) will be merged together to get a new FOR. Then, a load of a 24 Reliability Test System and a variant number of populations composed of PV system size is used to obtain the expected unserved energy (EUE) and loss of load expectation (LOLE). The EP technique for optimization is applied to determine the best sizing and generating unit (GU) of the PV system with the EUE close to zero and LOLE less than 2.4 hours per year. This paper used the effect of weather conditions on the PV system as a case analysis.