Day-ahead optimal dispatch of a virtual power plant in the joint energy-reserve-carbon market

Xuan Wei, Yinliang Xu, Hongbin Sun, Xiang Bai, Xinyue Chang and Yixun Xue

Applied Energy, 2024, vol. 356, issue C, No S0306261923018238

Abstract: As an efficient technique to manage massive distributed energy resources (DER), the virtual power plant (VPP) can leverage the aggregated flexibility to enhance the economy and security of the system. However, few efforts have been reported on the carbon emission reduction benefit of the VPP. In this paper, a novel incentive mechanism for low-carbon demand response is designed, which is based on dynamic pricing and carbon intensity. Considering the uncertainty of renewable energy output characterized by the chance-constrained approach, a coordinated optimization model in the joint day-ahead energy, reserve and carbon market for the VPP operator and flexible consumers is proposed, including the pre-dispatch model, the energy storage systems (ESSs) incorporated carbon emission flow calculation model, and the bi-level final-dispatch model. Numerical simulations of both small-scale and large-scale cases demonstrate that the proposed low-carbon dispatch strategy can boost the payoff of the VPP operator, reduce carbon emissions in the joint energy-reserve-carbon market, and improve the robustness of the power system against uncertainty.

Keywords: Virtual power plant; Chance-constrained; Carbon emission flow; Joint energy-reserve-carbon market; Demand response (search for similar items in EconPapers)
Date: 2024
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Citations: View citations in EconPapers (7)

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DOI: 10.1016/j.apenergy.2023.122459

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