Optimization planning of distributed generation and electric vehicle charging station using flower pollination algorithm

Abstract

In the world of electricity, the rapid development of technology causes the need for electrical energy to increase every year, followed by the challenge of using New and Renewable Energy to replace conventional energy sources. The integration of Distributed Generation (DG) and Electric Vehicle Charging Station (EVCS) into the distribution system has an effect on the electrical system such as the quality of the voltage profile and power losses. Apart from the electricity system, it also affects the economy and the environment. Therefore, it is necessary to determine the allocation and capacity of the DG and EVCS to obtain optimal and efficient planning for the electric power distribution system. The planning is carried out using the Flower Pollination Algorithm (FPA) optimization method by taking the research location in the East Sumba area feeder with 4 planning scenarios. In this study, real etap data for feeders in the East Sumba area were used which were then integrated with the OpenDSS and Matlab software. The best results obtained in scenario 1 are placing DG1 on BusUtamaA with a capacity of 1400 kW, DG2 on BusUtamaA with a capacity of 1010 kW, DG3 on Bus324 with a capacity of 1000 kW, and placing EVCS1 on Bus253 with a capacity of 1010 kW, EVCS2 on Bus324 with a capacity of 2510 kW, EVCS3 on BusUtamaA with a capacity of 2670 kW. The comparison results in the initial system and the 4 scenarios in terms of power losses and voltage profiles show that scenario 1 is the best plan compared to the other 3 scenarios. Based on research on these plans, it is hoped that the government and electrical company agencies will be able to consider the optimization method as a solution for planning future electricity system development.