Distributed Generation Management in Smart Grid with the Participation of Electric Vehicles with Respect to the Vehicle Owners’ Opinion by Using the Imperialist Competitive Algorithm

Abstract

In this paper, a modified version of Imperialist Competitive Algorithm (ICA) is proposed for the optimal energy management of a Microgrid (MG) with Parking Lots (PL) and Distributed Generation (DG) units. A 24-h scheduling for participation in DG units and electric vehicles PLs in two scenarios is done. The PLs are divided into seven group that each group has different trip behavior. Therefore, energy management should be done in such a way as to minimize operating costs according to the charging status of electric vehicles as well as the production capacity of distributed generation sources. Finally, the results of the two scenarios are reviewed separately and compared. The simulation results proved the effectiveness of the proposed method. The MG operation cost is decreased about 63%. Also, the optimization results. The optimization results by the proposed ICA algorithm are compared with the results of genetic algorithm (GA) and particle swarming optimization (PSO) algorithms. The optimization results confirm better performance of the proposed algorithm compared to GA and PSO algorithms.

Fuzzy-Energy-Management-Based Intelligent Direct Torque Control for a Battery—Supercapacitor Electric Vehicle

“…GA is a stochastic universal adaptive search optimization technique based on inherent selection [28][29][30][31]. In this algorithm, the chromosomes will mate through a process called crossover, producing offspring that combine their parent's genes.…”

Incentive Compensation Mechanism for the Infrastructure Construction of Electric Vehicle Battery Swapping Station under Asymmetric Information

“…Electric vehicles (EVs), which are powered by batteries instead of traditional fuels, are considered to have the capability to reduce the transportation sector's carbon emissions, improve consumer comfort, and protect the ecological environment [26]. Given these advantages above, the EVs' development has attracted extensive attention from governments, manufactures, consumers, environmentalists, academics, etc., [27]. However, the long battery charging time has seriously hindered the development of the EV industry.…”

Optimal placement of distribution network‐connected microgrids on multi‐objective energy management with uncertainty using the modified Harris Hawk optimization algorithm

“…Three possibilities are studied: reducing costs, reducing pollution, and reducing costs and pollution at the same time. Reference [26] proposes a modified version of the imperialist competitive algorithm (ICA) for the optimal energy management of a MG with parking lots (PL) and DG units. and covers a study on distributed generation management in a smart grid with the participation of electric vehicles (EVs) and using the ICA to optimize energy management.…”