Energy Cost Optimization of Hybrid Renewables Based V2G Microgrid Considering Multi Objective Function by Using Artificial Bee Colony Optimization

Habib Ur Rahman Habib; Umashankar Subramaniam; Asad Waqar; Bashar Sakeen Farhan; Kotb M. Kotb; Shaorong Wang

doi:10.1109/ACCESS.2020.2984537

IEEE Access (Jan 2020)

Energy Cost Optimization of Hybrid Renewables Based V2G Microgrid Considering Multi Objective Function by Using Artificial Bee Colony Optimization

Habib Ur Rahman Habib,
Umashankar Subramaniam,
Asad Waqar,
Bashar Sakeen Farhan,
Kotb M. Kotb,
Shaorong Wang

Affiliations

Habib Ur Rahman Habib: ORCiD; School of Electrical and Electronics Engineering, Huazhong University of Science and Technology, Wuhan, China
Umashankar Subramaniam: Renewable Energy Laboratory, College of Engineering, Prince Sultan University, Riyadh, Saudi Arabia
Asad Waqar: ORCiD; Department of Electrical Engineering, Bahria University, Islamabad, Pakistan
Bashar Sakeen Farhan: ORCiD; Electrical Engineering Department, Engineering College, Al-Iraqia University, Baghdad, Iraq
Kotb M. Kotb: ORCiD; Electrical Power and Machines Engineering Department, Faculty of Engineering, Tanta University, Tanta, Egypt
Shaorong Wang: ORCiD; School of Electrical and Electronics Engineering, Huazhong University of Science and Technology, Wuhan, China

DOI: https://doi.org/10.1109/ACCESS.2020.2984537
Journal volume & issue: Vol. 8
pp. 62076 – 62093

Abstract

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The worldwide demand for reduction of CO2 pollution, with more penetration of renewable energy sources and an increased number of electric vehicles (EVs), demonstrates the importance of economic dispatch (ED) with taking into account the reduction of CO2 emission. ED is a classical problem in which EVs impose more penetration as a dynamic load, and its impact as vehicle-to-grid (V2G) is the possible future trend with cost minimization. Based on the integration of EVs and hybrid renewable sources concerning both economic dispatch and pollution minimization, the multi-objective function is converted into a single comprehensive objective by using the judgment matrix methodology. In this paper, the investigation involves the minimization of the cost of all three objectives viz. operation cost, pollution cost, and carbon emissions with ED by incorporating V2G technology. The algorithms which include particle swarm optimization, as well as artificial bee colony, are applied under various operation and control strategies. The proposed models are verified and analyzed with different case studies. In terms of operation economics, the simulation results validate the superior performance of EVs based microgrid (MG) model in the coordinated charging and discharging mode. Further, the comparison of both algorithms shows better results with the ABC algorithm in terms of cost minimization of all objectives. ABC is better in V2G based microgrid with coordinated charging and discharging mode while its performance is significant during a large number of EVs (i.e., 700 EVs). Moreover, the load shedding scenarios are integrated which enables the MG system to operate in dual mode (i.e., seamless transition). In this paper, the main contribution involves penetration of EVs as dynamic load and its V2G impact in a coordinated or uncoordinated way, application of ABC algorithm for this particular load problem with improved results, and inclusion of short-term load shedding scenarios.

Published in IEEE Access

ISSN: 2169-3536 (Online)
Publisher: IEEE
Country of publisher: United States
LCC subjects: Technology: Electrical engineering. Electronics. Nuclear engineering
Website: https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=6287639

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