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考虑分时碳价的虚拟电厂分布鲁棒竞标方法

Distributionally robust bidding method for virtual power plant considering time-of-use carbon price
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摘要 为了探索双碳目标下虚拟电厂(virtual power plants,VPP)低碳、经济的竞标策略,提出了一种基于分时碳价和分布鲁棒优化思想的VPP参与日前多类市场的竞标策略。从减小电力市场运营成本的角度,提出了一种与电价负相关的分时碳价,采用基准线法为VPP无偿分配碳配额,计算新能源发电的国家核证减排量;综合考虑碳交易市场、能量市场和调峰市场的情况,搭建了VPP参与多类市场的竞标模型;针对风电的不确定性,构建了基于数据驱动的分布鲁棒两阶段竞标模型,并采用列与约束生成算法求解。算例分析表明,分时碳价能够有效降低电力市场运营商的运行成本,提高VPP运营商的收益,所提的VPP竞标模型能给出不同市场的最优投标方案,而分布鲁棒能够兼顾经济性与鲁棒性。 In order to explore the low-carbon and economic bidding strategy of virtual power plant(VPP)under dual carbon targets,this paper proposed a bidding strategy of VPP participating in day-ahead multi-class market based on time-of-use carbon price and distributionally robust optimization.Firstly,in order to reduce the operating cost of electricity market,a time-of-use carbon price negatively related to electricity price is proposed.Then,the baseline method is adopted to allocate carbon quota for VPP free of charge,and the national certified emission reduction of new energy power generation is calculated.Secondly,considering the situation of carbon trading market,energy market and peak regulating market,the bidding model of VPP participating in multiple markets is set up.Finally,aiming at the uncertainty of wind power,a data-driven two-stage bidding model of blue-bar is constructed and solved by column and constraint generation algorithm.The example analysis shows that time-of-use carbon price can effectively reduce the operating cost of electricity market operators and improve the revenue of VPP operators.The proposed VPP bidding model can give the optimal bidding scheme of different markets,and the distributed robust can give consideration to both economy and robustness.
作者 刘亚鑫 蔺红 马越 朱彦祥 LIU Yaxin;LIN Hong;MA Yue;ZHU Yanxiang(School of Electrical Engineering,Xinjiang University,Urumqi 830017,China)
出处 《电测与仪表》 北大核心 2024年第8期12-19,共8页 Electrical Measurement & Instrumentation
基金 新疆维吾尔自治区重点研发专项(2022B01020-3)。
关键词 虚拟电厂 分时碳价 能量市场 调峰市场 分布鲁棒优化 virtual power plants time-of-use carbon price energy market peak regulating market distributionally robust optimization
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