Reducing power loss considering massive charging station using metaheuristic technique

Abstract

As a member of the Paris agreement, Malaysia is committed to transforming into a low-carbon society. The Malaysian government aims to reduce greenhouse gas emissions by 45% on 2030. The Malaysian government is promoting energy-efficient vehicles (EEV) including future electric vehicles (EV), and aims to have 100% of EEV on-road by 2030. With the implementation of EV policies in Malaysia, these policies will act as an agitator for the mass adoption of EVs in Malaysian usage. However, from the viewpoint of the power system, EVs are additional loads when connect to the power grid. The massive penetration of charging station (CS) load has negatively impacted the distribution system, especially on the power losses. Hence, this situation has led to the need for unifying rules for the distribution system to accommodate this additional charging demand. In this research, the mitigation proposed is to implement optimal placement and sizing of multiple capacitor banks (CBs) for medium and low voltage distribution network systems optimized using the metaheuristic technique. The distribution system, CS and CBs are modelled using MATLAB environment. The metaheuristic technique used is Lightning Search Algorithm (LSA) and Modified Lightning Search Algorithm (MLSA) due to effectiveness from past research. Based on the simulation result, the MLSA method will best minimize the power losses at the practical 69-bus radial distribution network system. The study has proven that the optimal placement and sizing of variable CBs could reduce power loss. Furthermore, the results demonstrate that the multiple of CBs can provide a superior solution compared to a single CB. Hence, it concluded that the multiple CBs with the assistance of the MLSA method are the most suitable to be implemented in reducing power losses in distribution systems due to the massive penetration of EVs load.