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Optimal Allocation Model of Virtual Power Plant Capacity considering Electric Vehicles

Author

Listed:
  • Shiping Geng
  • Caixia Tan
  • Dongxiao Niu
  • Xiaopeng Guo

Abstract

To push forward the development of electric vehicles while improving the economy and environment of virtual power plants (VPPs), research on the optimization of VPP capacity considering electric vehicles is carried out. In this paper, based on this, this paper first analyzes the framework of the VPP with electric vehicles and models each unit of the VPP. Secondly, the typical scenarios of wind power, photovoltaic, electric vehicle charging and discharging, and load are formed by the Monte Carlo method to reduce the output deviation of each unit. Then, taking the maximization of the net income and clean energy consumption of the VPP as the objective function, the capacity optimal allocation model of the VPP considering multiobjective is constructed, and the conditional value-at-risk (CVaR) is introduced to represent the investment uncertainty faced by the VPP. Finally, a VPP in a certain area of Shanxi Province is used to analyze a calculation example and solve it with CPLEX. The results of the calculation example show that, on the one hand, reasonable selection of the optimal scale of EV connected to the VPP is able to improve the economy and environment of the VPP. On the other hand, the introduction of CVaR is available for the improvement of the scientific nature of VPP capacity allocation decisions.

Suggested Citation

  • Shiping Geng & Caixia Tan & Dongxiao Niu & Xiaopeng Guo, 2021. "Optimal Allocation Model of Virtual Power Plant Capacity considering Electric Vehicles," Mathematical Problems in Engineering, Hindawi, vol. 2021, pages 1-19, June.
    • Handle: RePEc:hin:jnlmpe:5552323
    DOI: 10.1155/2021/5552323
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    Cited by:

    1. Bai, Hanyu & Lei, Shunbo & Geng, Sijia & Hu, Xiaosong & Li, Zhaojian & Song, Ziyou, 2024. "Techno-economic assessment of isolated micro-grids with second-life batteries: A reliability-oriented iterative design framework," Applied Energy, Elsevier, vol. 364(C).
    2. Shahid Nawaz Khan & Syed Ali Abbas Kazmi & Abdullah Altamimi & Zafar A. Khan & Mohammed A. Alghassab, 2022. "Smart Distribution Mechanisms—Part I: From the Perspectives of Planning," Sustainability, MDPI, vol. 14(23), pages 1-109, December.
    3. Hongyang He & Zhigang Lu & Xiaoqiang Guo & Changli Shi & Dongqiang Jia & Chao Chen & Josep M. Guerrero, 2022. "Optimized Control Strategy for Photovoltaic Hydrogen Generation System with Particle Swarm Algorithm," Energies, MDPI, vol. 15(4), pages 1-17, February.

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