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Optimal Dispatch of a Virtual Power Plant Considering Demand Response and Carbon Trading

Author

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  • Zuoyu Liu

    (School of Electrical Engineering, Zhejiang University, No. 38 Zheda Rd., Hangzhou 310027, China)

  • Weimin Zheng

    (State Grid Zhejiang Electric Power Co., Ltd., No. 8 Huanglong Rd., Hangzhou 310007, China)

  • Feng Qi

    (School of Electrical Engineering, Zhejiang University, No. 38 Zheda Rd., Hangzhou 310027, China)

  • Lei Wang

    (State Grid Zhejiang Economic Research Institute, No.1 Nanfu Road, Hangzhou 310008, China)

  • Bo Zou

    (State Grid Zhejiang Economic Research Institute, No.1 Nanfu Road, Hangzhou 310008, China)

  • Fushuan Wen

    (Department for Management of Science and Technology Development, Ton Duc Thang University, Ho Chi Minh City, Vietnam
    Faculty of Electrical and Electronics Engineering, Ton Duc Thang University, Ho Chi Minh City, Vietnam)

  • You Xue

    (School of Electrical Engineering, Zhejiang University, No. 38 Zheda Rd., Hangzhou 310027, China)

Abstract

The implementation of demand response (DR) could contribute to significant economic benefits meanwhile simultaneously enhancing the security of the concerned power system. A well-designed carbon emission trading mechanism provides an efficient way to achieve emission reduction targets. Given this background, a virtual power plant (VPP) including demand response resources, gas turbines, wind power and photovoltaics with participation in carbon emission trading is examined in this work, and an optimal dispatching model of the VPP presented. First, the carbon emission trading mechanism is briefly described, and the framework of optimal dispatching in the VPP discussed. Then, probabilistic models are utilized to address the uncertainties in the predicted generation outputs of wind power and photovoltaics. Demand side management (DSM) is next implemented by modeling flexible loads such as the chilled water thermal storage air conditioning systems (CSACSs) and electric vehicles (EVs). On this basis, a mixed integer linear programming (MILP) model for the optimal dispatching problem in the VPP is established, with an objective of maximizing the total profit of the VPP considering the costs of power generation and carbon emission trading as well as charging/discharging of EVs. Finally, the developed dispatching model is solved by the commercial CPLEX solver based on the YALMIP/MATLAB (version 8.4) toolbox, and sample examples are served for demonstrating the essential features of the proposed method.

Suggested Citation

  • Zuoyu Liu & Weimin Zheng & Feng Qi & Lei Wang & Bo Zou & Fushuan Wen & You Xue, 2018. "Optimal Dispatch of a Virtual Power Plant Considering Demand Response and Carbon Trading," Energies, MDPI, vol. 11(6), pages 1-19, June.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:6:p:1488-:d:151169
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    References listed on IDEAS

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    5. Guoqiang Sun & Weihang Qian & Wenjin Huang & Zheng Xu & Zhongxing Fu & Zhinong Wei & Sheng Chen, 2019. "Stochastic Adaptive Robust Dispatch for Virtual Power Plants Using the Binding Scenario Identification Approach," Energies, MDPI, vol. 12(10), pages 1-23, May.
    6. Jesse G. Wales & Alexander J. Zolan & William T. Hamilton & Alexandra M. Newman & Michael J. Wagner, 2023. "Combining simulation and optimization to derive operating policies for a concentrating solar power plant," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 45(1), pages 119-150, March.
    7. Peng Wang & Meng Li, 2019. "Scenario Analysis in the Electric Power Industry under the Implementation of the Electricity Market Reform and a Carbon Policy in China," Energies, MDPI, vol. 12(11), pages 1-26, June.
    8. Mohammad Mohammadi Roozbehani & Ehsan Heydarian-Forushani & Saeed Hasanzadeh & Seifeddine Ben Elghali, 2022. "Virtual Power Plant Operational Strategies: Models, Markets, Optimization, Challenges, and Opportunities," Sustainability, MDPI, vol. 14(19), pages 1-23, September.
    9. Huiru Zhao & Chao Zhang & Yihang Zhao & Xuejie Wang, 2022. "Low-Carbon Economic Dispatching of Multi-Energy Virtual Power Plant with Carbon Capture Unit Considering Uncertainty and Carbon Market," Energies, MDPI, vol. 15(19), pages 1-25, October.
    10. Wafa Nafkha-Tayari & Seifeddine Ben Elghali & Ehsan Heydarian-Forushani & Mohamed Benbouzid, 2022. "Virtual Power Plants Optimization Issue: A Comprehensive Review on Methods, Solutions, and Prospects," Energies, MDPI, vol. 15(10), pages 1-20, May.
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