Optimal V2G and G2V Scheduling for Cost-Effective Power Management in Distribution System

• Published in: 2024 IEEE 4th International Conference on Sustainable Energy and Future Electric Transportation (SEFET) pp. 1 - 6
• Main Authors: Yadav, Nil Kamal, Das, Soumyabrata
• Format: Conference Proceeding
• Language: English
• Published: IEEE 31-07-2024
• Subjects: Competitive Swarm Optimizer; Costs; Electric vehicle charging; Electric Vehicles; Electricity; Genetic algorithms; Optimal scheduling; Power grids; Power Purchase Cost; Power system management; Radial Distribution System; Reliability; Transportation; Vehicle-to-grid
• DOI: 10.1109/SEFET61574.2024.10718089

Electric vehicles (EVs) offer a eco-friendly solution to the transportation sector, promoting energy efficiency, minimized fossil fuel dependency, and reduced greenhouse gas emissions. Optimal scheduling of EV charging contributes significantly to the efficient and reliable operation of the electricity grid. In this paper, priority based Vehicle-to-Grid and Grid-to-Vehicle optimization scheduling is proposed with the objective of minimizing the power purchase cost from the power grid. The proposed approach aims to maximize the profits of both the EV owners and the distribution system operator. Competitive Swarm Optimizer (CSO) algorithm with several electrical considerations and limitations has been adopted to solve the optimization problem. Here, optimization works in two mode- valley filling mode and peak shaving mode. The aim of the work is to shift the peak load to off-peak period by proper charging and discharging scheduling of EVs in order to reduce the electricity prices. Load variance is also reduced by shifting the peak load to the off-peak period. Further, the results obtained though CSO algorithm are compared with the other algorithms such as Bat algorithm, Genetic Algorithm and Salp Swarm Algorithm. IEEE 34-bus RDS is used as a test system for the validation of results. The percentage reduction in electricity expenses compared to pre-scheduling using CSO is 1.34%.