Addressing the economic dispatch solution of a smart microgrid with a developed charging strategy for electric vehicles with demand-side response

Abstract

Reducing the operation cost and the dependence on fossil fuel-based energy resources is a crucial task in electric power systems, which can be accomplished via optimal economic dispatch (ED) problem solutions. In this regard, this work proposed a new modified dandelion optimizer (MDO) for solving the ED of a grid-connected microgrid, which consists of a diesel generator, three fuel cells (FCs), and two wind turbines to provide the required energy to electric loads and an electric vehicle (EV) charging station. The MDO is mainly based on two approaches, including the fitness distance balance and local elite movement to emphasize the searching ability of the conventional DO. In this chapter, a smart strategy is proposed for reducing the operation costs, which is based on the application of a demand-side response-based real-time price and a smart charging strategy for EVs, which is based on maximizing and controlling the charging powers of EVs at each hour instead of charging the EVs by uncontrolled power. The results reveal that the MDO is superior for ED solution compared to the grey wolf optimizer, whale optimization algorithm, sand cat swarm optimizers, and dandelion optimizer. In addition to that the cost is reduced considerably with the application of the smart strategy. Additionally, the operating cost is reduced considerably via the application of the DSR and the smart charging strategy.