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  • 标题:Optimal Peak Regulation Strategy of Virtual and Thermal Power Plants
  • 本地全文:下载
  • 作者:Peng Li ; Yuanfeng Chen ; Kang Yang
  • 期刊名称:Frontiers in Energy Research
  • 电子版ISSN:2296-598X
  • 出版年度:2022
  • 卷号:10
  • DOI:10.3389/fenrg.2022.799557
  • 语种:English
  • 出版社:Frontiers Media S.A.
  • 摘要:To achieve the national carbon-peak and carbon-neutral strategic development goals, it is necessary to build power systems dominated by renewable and sustainable energy. The future power system with a high proportion of renewable and sustainable energy is required to have large-scale, low-cost, flexible, and adjustable resources. To this end, this article aggregates user-side distributed energy storage and electric vehicles into a virtual power plant, considering the uncertainty of wind power fluctuations and the uncertainty of electric vehicle charging and discharging to establish a day-ahead and intra-day peak regulation model for combined peak regulation of virtual and thermal power plants. The bounding algorithm seeks the optimal strategy for the two-stage model of joint peak regulation and obtains the day-ahead and intra-day two-stage optimal peak regulation strategy. The simulation example shows that the virtual power plant and its day-ahead and intra-day optimal peak regulation strategy can reduce the peak regulation cost of the power system, as compared with the deep peak regulation of thermal power plants with a special supporting energy storage power station. This work provides a global perspective for virtual power plants to participate in the formulation of power system peak regulation rules.
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