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1.智慧城市物联网国家重点实验室(澳门大学),澳门 999078
2.浙江大学电气工程学院,浙江省杭州市 310027
3.深圳供电局有限公司,广东省深圳市 518001
Received:13 March 2024,
Revised:2024-05-29,
Published Online:24 July 2024,
Published:25 September 2024
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QI Taoyi,HUI Hongxun,YE Chengjin,et al.Bidding Mechanism Design for Building Virtual Power Plant to Participate in Demand Response Markets[J].Automation of Electric Power Systems,2024,48(18):14-24.
漆淘懿,惠红勋,叶承晋等.建筑虚拟电厂参与需求响应市场的报量报价机制设计[J].电力系统自动化,2024,48(18):14-24. DOI: 10.7500/AEPS20240313002.
QI Taoyi,HUI Hongxun,YE Chengjin,et al.Bidding Mechanism Design for Building Virtual Power Plant to Participate in Demand Response Markets[J].Automation of Electric Power Systems,2024,48(18):14-24. DOI: 10.7500/AEPS20240313002.
高负荷密度的受端城市电网正面临日益严重的调节资源匮乏问题,城市建筑拥有大量中央空调、电动汽车等优质灵活资源,可通过聚合构建虚拟电厂参与城市电网的供需互动。随着需求响应市场的快速发展,灵活资源的市场化定价和交易成为趋势。为此,考虑到建筑和虚拟电厂两者的获益需求,设计了建筑虚拟电厂参与需求响应市场交易的报量报价机制。首先,根据建筑负荷的响应特性,将其分为无损可转移负荷、有损可转移负荷和有损可削减负荷,并分别提出其容量-成本的计算方法。然后,设计了同时保证建筑和虚拟电厂可靠收益的分配方法,以持续激励两者参与市场的积极性。在此基础上,建立了虚拟电厂参与市场交易的报价优化模型,实现不同场景下虚拟电厂的收益最大化。最后,通过算例仿真证明了所提机制在市场交易和收益分配方面的有效性。
The receiving-end urban power grids with high load density are facing an increasingly serious shortage of regulation resource. Urban buildings have many promising and flexible resources such as central air conditioners and electric vehicles
and can participate in the supply-demand interaction by constructing the virtual power plant (VPP) through aggregation. With the rapid development of the demand response (DR) markets
the market-oriented pricing and trading of flexible resources have become a trend. Therefore
considering the benefit demand of buildings and VPPs
the bidding mechanism for the building VPP participating in the DR market trading is designed. First
according to the characteristics of flexible loads of buildings
they are divided into lossless transferable loads
lossy transferable loads
as well as lossy reducible loads
and the corresponding formulation methods of capacity-cost are proposed
respectively. Then
an allocation method is proposed to guarantee the reliable revenues of both the buildings and the VPP
so as to continuously motivate them to participate in the DR markets. On this basis
the bidding optimization model is developed for the VPP to participate in the DR markets to realize the maximization of the revenues of VPPs in different scenarios. Finally
the effectiveness of the proposed mechanism in market trading and revenues allocation is proved by case simulations.
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