Optimal EV Battery Storage Exploitation for Energy Conservation in Low Voltage Distribution Network

The storage capacity of Electric Vehicles (EVs) can be used to improve energy management in low-voltage distribution networks. The research throughout the previous decade has concentrated on several control strategies for grid auxiliary assistance via Vehicle-to-Grid (V2G) and Grid-to-Vehicle (G2V). This article focuses on energy management in distribution networks using EVs, solar photovoltaic (PV), and diesel generators (DG). To begin with, Water Filling Algorithm (WFA) is utilized to disperse EV storage optimally in each zone of energy needed for load flattening. The goal here is to decrease grid reliance while minimizing overall energy costs. After that, a win–win plan is formed between the EV owner and the grid operator to lower EV charging costs and increase EV storage usage for grid support. A multi-Objective Optimization problem is formulated with two objectives: load flattening and voltage regulation. This is solved by Multi-Objective Genetic Algorithm (MOGA) where the decision variable is EV power transaction, Optimal Power Transaction (OPT). ANFIS-based EV ranking technique has been designed to achieve these two aims concurrently. The influence of Optimal Energy Distribution (OED) has been studied in different scenarios. ANFIS prioritization is investigated in several scenarios, as well as the impact on overall EV power availability and Cost of Charging (CoC).