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1.新能源电力系统全国重点实验室(华北电力大学),北京市 102206
2.国网天津市电力公司城西供电分公司,天津市 300110
高雪倩(1997—),女,通信作者,博士研究生,主要研究方向:新型电力系统规划调度与风险评估、电力市场。E-mail:gaoxueqian2019@163.com
刘畅(1996—),女,硕士,主要研究方向:综合能源系统规划与可靠性。E-mail:liuchangncepu@163.com
刘文霞(1967—),女,博士,教授,博士生导师,主要研究方向:电力系统规划与可靠性、电力系统风险评估、信息物理系统等。E-mail:liuwenxia001@163.com
收稿:2024-01-20,
修回:2024-05-24,
网络出版:2024-09-27,
纸质出版:2024-10-25
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高雪倩,刘畅,刘文霞.计及备用优化的电热灵活性资源协同鲁棒规划[J].电力系统自动化,2024,48(20):171-181.
GAO Xueqian,LIU Chang,LIU Wenxia.Collaborative Robust Planning of Electric and Thermal Flexibility Resources Considering Reserve Optimization[J].Automation of Electric Power Systems,2024,48(20):171-181.
高雪倩,刘畅,刘文霞.计及备用优化的电热灵活性资源协同鲁棒规划[J].电力系统自动化,2024,48(20):171-181. DOI: 10.7500/AEPS20240120002.
GAO Xueqian,LIU Chang,LIU Wenxia.Collaborative Robust Planning of Electric and Thermal Flexibility Resources Considering Reserve Optimization[J].Automation of Electric Power Systems,2024,48(20):171-181. DOI: 10.7500/AEPS20240120002.
在中国的“三北”地区,风资源丰富,系统灵活性资源匮乏,供暖期系统内热电占比高,挤占风电上网空间,给系统安全经济运行带来严峻挑战。为提高风电消纳的经济性,文中提出了一种计及备用优化的电热灵活性资源协同鲁棒规划方法。首先,研究各类资源促进热电解耦调峰运行机理及其协同规划机理。在此基础上,建立了min-max-min三层两阶段轻鲁棒规划模型。主问题以规划目标年增量投资成本、运行成本和备用不足风险成本之和最小为目标,优化各类资源投资方案和日前确定性优化调度;子问题在日前调度结果的基础上,计及风电不确定性,以最恶劣场景下备用不足风险最小为目标在日内对设备进行重新调度,搜寻最恶劣场景并评估备用不足风险。基于列与约束生成算法与强对偶理论,进行主、子问题迭代求解。最后,算例验证了模型有效性,并对模型的鲁棒性和风险进行分析。
In the “Three North” regions of China
wind resources are abundant but system flexibility resources are scarce. During the heating period
the proportion of electric output of thermoelectric unit is high
affecting wind power integration and posing severe challenges to the safe and economic operation of the system. To improve the economy of wind power accommodation
a collaborative robust planning method for electric and thermal flexibility resources considering reserve optimization is proposed. First
the peak shaving operation mechanism of promoting thermoelectric decoupling and its collaborative planning mechanism through various resources has been studied. On this basis
a min-max-min three-layer two-stage light robust planning model is established. The main problem aims to minimize the sum of the planned annual incremental investment cost
operation cost
and risk cost of insufficient reserve
optimizes all kinds of resource investment schemes and day-ahead deterministic optimal scheduling. Taking into account the uncertainty of wind power based on day-ahead scheduling results
the sub-problem minimizes the risk of insufficient reserve in the worst scenario
reschedule the equipment within days
searches for the worst scenario
and assesses the risk of insufficient reserve. The main problem and sub-problems are solved iteratively based on the column-and-constraint generation algorithm and the strong duality theory. Finally
the validity of the model is verified by a numerical case
and the robustness and risk of the model are analyzed.
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