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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

Author

Listed:
  • Hassan Shokouhandeh

    (Department of Electrical Engineering, Semnan University, Semnan 35131-19111, Iran)

  • Mehrdad Ahmadi Kamarposhti

    (Department of Electrical Engineering, Jouybar Branch, Islamic Azad University, Jouybar 47761-86131, Iran)

  • Fariba Asghari

    (Department of Electrical Engineering, Ilam Branch, Islamic Azad University, Ilam 61349-37333, Iran)

  • Ilhami Colak

    (Department of Electrical and Electronics Engineering, Faculty of Engineering and Architectures, Nisantasi University, Istanbul 25370, Turkey)

  • Kei Eguchi

    (Department of Information Electronics, Fukuoka Institute of Technology, Fukuoka 811-0295, Japan)

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.

Suggested Citation

  • Hassan Shokouhandeh & Mehrdad Ahmadi Kamarposhti & Fariba Asghari & Ilhami Colak & Kei Eguchi, 2022. "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," Sustainability, MDPI, vol. 14(8), pages 1-17, April.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:8:p:4770-:d:795104
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    References listed on IDEAS

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    2. Hassan Shokouhandeh & Mehrdad Ahmadi Kamarposhti & Ilhami Colak & Kei Eguchi, 2021. "Unit Commitment for Power Generation Systems Based on Prices in Smart Grid Environment Considering Uncertainty," Sustainability, MDPI, vol. 13(18), pages 1-13, September.
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    Cited by:

    1. Adel Oubelaid & Hisham Alharbi & Abdullah S. Bin Humayd & Nabil Taib & Toufik Rekioua & Sherif S. M. Ghoneim, 2022. "Fuzzy-Energy-Management-Based Intelligent Direct Torque Control for a Battery—Supercapacitor Electric Vehicle," Sustainability, MDPI, vol. 14(14), pages 1-20, July.
    2. Mohammad Kamrul Hasan & AKM Ahasan Habib & Shayla Islam & Mohammed Balfaqih & Khaled M. Alfawaz & Dalbir Singh, 2023. "Smart Grid Communication Networks for Electric Vehicles Empowering Distributed Energy Generation: Constraints, Challenges, and Recommendations," Energies, MDPI, vol. 16(3), pages 1-20, January.
    3. Huibing Cheng & Shanshui Zheng, 2022. "Incentive Compensation Mechanism for the Infrastructure Construction of Electric Vehicle Battery Swapping Station under Asymmetric Information," Sustainability, MDPI, vol. 14(12), pages 1-18, June.
    4. Polisetty, S.P.R. Swamy & Jayanthi, R. & Sai Veerraju, M., 2023. "An intelligent optimal charging stations placement on the grid system for the electric vehicle application," Energy, Elsevier, vol. 285(C).

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