Interval Optimization Technique Based Multi-Objective Scheduling of Electric Vehicles

Abstract

Increasing penetration of electric vehicles (EVs) mandates the adoption of scheduling strategies to mitigate adverse effects of their charging load on distribution system. EVs scheduling is a multi-objective problem where the objectives fall in the interest of either EV users or distribution system operator (DSO). Therefore, this paper aims to deal with multi-objective scheduling of EVs to couple the interest of both the entities. To consider the interest of EV users, an economic objective of minimizing the charging cost is considered whereas to address the interest of DSO a technical objective of load levelling is considered. A multi-objective grey wolf optimization (MOGWO) is used to handle the conflicting objectives followed by technique for order preference by similarity to ideal solution (TOPSIS) based approach for obtaining trade-off solution. In addition, uncertainty in forecasted load demand and electricity price is handled using interval optimization. Results show that EVs scheduling with interval optimization is more robust as compared to optimistic and pessimistic cases.