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作 者:李咸善[1] 仇成龙 张远航 王秋杰[2] 李飞[1,3] LI Xianshan;QIU Chenglong;ZHANG Yuanhang;WANG Qiujie;LI Fei(Hubei Provincial Key Laboratory of Operation and Control of Cascade Hydropower Stations(China Three Gorges University),Yichang 443002,China;School of Electrical Engineering and New Energy,China Three Gorges University,Yichang 443002,China;State Key Laboratory of Water Resources Engineering and Management,Wuhan University,Wuhan 430072,China)
机构地区:[1]梯级水电站运行与控制湖北省重点实验室(三峡大学),湖北宜昌443002 [2]三峡大学电气与新能源学院,湖北宜昌443002 [3]水资源工程与调度全国重点实验室(武汉大学),湖北武汉430072
出 处:《电力系统保护与控制》2025年第6期163-174,共12页Power System Protection and Control
基 金:国家自然科学基金项目资助(52307109);水资源工程与调度全国重点实验室开放基金项目资助(2023SDG02)。
摘 要:电动汽车EV聚合商(EV aggregator,EVA)申报国家自愿减排(Chinese certified emission reduction,CCER)项目,响应电网低碳调度,可促进EVA高效运营和电力系统低碳转型。为此,提出了考虑电碳需求响应的EVA多市场运营策略。首先,基于碳排放流理论,构建了基于用电动态碳排放因子的EVA用能碳排模型,以及考虑电碳需求响应的EVA“电-碳”市场效益模型。其次,构建市场运营商与EVA之间的博弈模型。上层为市场出清模型,电力市场运营商以用能成本最小为目标进行市场出清,发布出清结果及用电动态碳排放因子。下层为EVA市场竞标决策模型,根据市场出清结果及用电动态碳排放因子,以效益最大化为目标制定用能计划竞标策略。最后,通过算例分析,验证了所提策略的有效性。Electric vehicle aggregators(EVA)that participate in Chinese certified emission reduction(CCER)projects in response to low-carbon dispatching can enhance efficient EVA operation while supporting the low-carbon transition of power systems.To achieve this,a multi-market EVA operational strategy considering electricity-carbon demand response is proposed.First,based on carbon emission flow theory,an EVA energy consumption carbon emission model is constructed based on the dynamic electricity carbon emission factors,and an EVA“electricity-carbon”market benefit model considering electricity-carbon demand response is developed.Next,a game model between market operators and EVAs is established.The upper layer represents the market clearing process,where electricity market operators minimize energy consumption costs,clear the market,and publish clearing results and dynamic electricity carbon emission factors.The lower layer is the EVA market bidding decision-making process,where EVAs formulate energy consumption bidding strategies to maximize their benefits according to the market clearing results and dynamic electricity carbon emission factors.Finally,the effectiveness of the proposed strategy is verified by a numerical example.
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