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A Hybrid Multi-Objective Crisscross Optimization for Dynamic Economic/Emission Dispatch Considering Plug-In Electric Vehicles Penetration

Author

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  • Panpan Mei

    (School of Information and Electrical Engineering, Hunan University of Science and Technology, Xiangtan 411201, China)

  • Lianghong Wu

    (School of Information and Electrical Engineering, Hunan University of Science and Technology, Xiangtan 411201, China)

  • Hongqiang Zhang

    (School of Information and Electrical Engineering, Hunan University of Science and Technology, Xiangtan 411201, China)

  • Zhenzu Liu

    (School of Information and Electrical Engineering, Hunan University of Science and Technology, Xiangtan 411201, China)

Abstract

Due to the significant uncertainty of charging time and charging power consumption, the large increase in plug-in electric vehicles (PEVs) may create a major influences on the power system: According to people’s living habits, PEVs are basically charged during peak load periods (after work). Once PEVs continue the random charging behavior, there will be a higher difference of peak-valley and bigger burden on the grid. A new strategy is put forward for dynamic economic/emission dispatch (DEED) with the consideration of PEVs for the purpose to shave the peak and fill the valley in this paper, and the influences brought from different loads of grid-to-vehicle (G2V) and vehicle-to-grid (V2G) on DEED problem are discussed. The problem to be solved is a challenging multi-objective non-linear problem. By taking advantage of the differential evolution (DE) algorithms and a newly developed crisscross optimization algorithm, a new multi-objective hybrid optimization algorithm is put forward to deal with the problem including effectively dealing with the inequality and equality constraints. A case study is presented to show the feasibility and effectiveness of the put forward method. The analysis results demonstrate that the put forward algorithm could effectively solve DEED problem, showing that the resulting approach of peak shaving and valley filling could significantly save economic costs and reduce emissions under the same load.

Suggested Citation

  • Panpan Mei & Lianghong Wu & Hongqiang Zhang & Zhenzu Liu, 2019. "A Hybrid Multi-Objective Crisscross Optimization for Dynamic Economic/Emission Dispatch Considering Plug-In Electric Vehicles Penetration," Energies, MDPI, vol. 12(20), pages 1-21, October.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:20:p:3847-:d:275370
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    References listed on IDEAS

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    Cited by:

    1. Ioannis Skouros & Athanasios Karlis, 2020. "A Study on the V2G Technology Incorporation in a DC Nanogrid and on the Provision of Voltage Regulation to the Power Grid," Energies, MDPI, vol. 13(10), pages 1-23, May.
    2. Saleh Aghajan-Eshkevari & Sasan Azad & Morteza Nazari-Heris & Mohammad Taghi Ameli & Somayeh Asadi, 2022. "Charging and Discharging of Electric Vehicles in Power Systems: An Updated and Detailed Review of Methods, Control Structures, Objectives, and Optimization Methodologies," Sustainability, MDPI, vol. 14(4), pages 1-31, February.
    3. Oracio I. Barbosa-Ayala & Jhon A. Montañez-Barrera & Cesar E. Damian-Ascencio & Adriana Saldaña-Robles & J. Arturo Alfaro-Ayala & Jose Alfredo Padilla-Medina & Sergio Cano-Andrade, 2020. "Solution to the Economic Emission Dispatch Problem Using Numerical Polynomial Homotopy Continuation," Energies, MDPI, vol. 13(17), pages 1-15, August.
    4. Zhang, Qiang & Zou, Dexuan & Duan, Na, 2023. "An improved differential evolution using self-adaptable cosine similarity for economic emission dispatch," Energy, Elsevier, vol. 283(C).

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