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1.强电磁工程与新技术国家重点实验室(华中科技大学),湖北省武汉市 430074
2.中国南方电网电力调度控制中心,广东省广州市 510623
3.华中科技大学中欧清洁与可再生能源学院,湖北省武汉市 430074
何翔路(1997—),女,硕士研究生,主要研究方向:电力市场、电力系统优化规划。E-mail:m201971387@hust.edu.cn
娄素华(1974—),女,通信作者,教授,博士生导师,主要研究方向:电力系统规划及电力系统运行。E-mail:shlou@hust.edu.cn
吴耀武(1963—),男,博士,副教授,硕士生导师,主要研究方向:电力系统规划及电力系统运行。E-mail:ywwu@mail.hust.edu.cn
收稿:2021-07-05,
修回:2021-08-26,
网络出版:2021-10-20,
纸质出版:2022-02-25
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何翔路,娄素华,吴耀武等.双结算模式下风储一体化电站两阶段市场投标调度策略[J].电力系统自动化,2022,46(4):47-55.
HE Xianglu,LOU Suhua,WU Yaowu,et al.Two-stage Market Bidding and Scheduling Strategy of Integrated Wind Power and Energy Storage Station in Dual-settlement Mode[J].Automation of Electric Power Systems,2022,46(4):47-55.
何翔路,娄素华,吴耀武等.双结算模式下风储一体化电站两阶段市场投标调度策略[J].电力系统自动化,2022,46(4):47-55. DOI: 10.7500/AEPS20210705005.
HE Xianglu,LOU Suhua,WU Yaowu,et al.Two-stage Market Bidding and Scheduling Strategy of Integrated Wind Power and Energy Storage Station in Dual-settlement Mode[J].Automation of Electric Power Systems,2022,46(4):47-55. DOI: 10.7500/AEPS20210705005.
随着中国电力现货市场建设进程不断加快,风电等新能源参与现货市场竞争已成为趋势,风储一体化电站作为未来风力发电站的一种发展形式,可以通过合理调控实现最大化收益。基于中国电力现货市场初期,双结算模式和偏差考核长期并存的结算规则,综合考量发电商在日前市场的投标收益以及在实时平衡市场的机会收益,建立了考虑储能寿命影响的风储一体化电站参与日前市场投标模型和实时平衡市场滚动自调度模型,以实现现货市场全出清尺度的决策优化。然后,采用随机-鲁棒相结合的建模方法描述日前、实时电价和风电出力的不确定性以优化决策效果。在此基础上,研究了储能寿命模型、鲁棒控制系数和发电预测能力对收益的影响,算例结果验证了所述模型与方法的有效性。
With the accelerating process of electricity spot market construction in China
it has become a trend for renewable energy sources such as wind power to participate in spot market competition. As a development mode of future wind power stations
integrated wind power and energy storage stations can maximize the revenue through reasonable regulation and control. Based on the long-term coexistence of dual-settlement mode and deviation assessment in the early stage of the electricity spot market in China
this paper comprehensively considers the bidding revenue in the day-ahead market and the opportunity revenue in the real-time balance market of power suppliers. Considering the impact of energy storage life
a bidding model in the day-ahead market and a rolling self-dispatching model in the real-time balance market are established with the participation of integrated wind power and energy storage stations
which realize the decision-making optimization of the spot market during all clearing scales. Then
the stochastic-robust modeling method is used to describe the day-ahead and real-time market prices and the uncertainty of the wind power output to optimize decision-making effects. On this basis
the effects of the energy storage life model
robust control coefficient and forecasting capabilities of power generation on the revenue are studied. The case results verify the effectiveness of the proposed model and method.
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