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湖南大学电气与信息工程学院,湖南省长沙市 410082
杜敏(1994—),男,博士研究生,主要研究方向:电力系统网络安全、电力系统韧性增强、电力系统安全经济调度等。E-mail:dumin94@hnu.edu.cn
刘绚(1985—),男,通信作者,博士,教授,博士生导师,主要研究方向:电力系统网络安全、配电网自动化、人工智能在电力系统中的应用等。E-mail:xliu@hnu.edu.cn
周元刚(1996—),男,硕士研究生,主要研究方向:电网信息安全、变电站数据加解密。E-mail:2545066372@hnu.edu.cn
收稿:2022-03-21,
修回:2022-06-20,
网络出版:2022-10-24,
纸质出版:2023-06-25
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杜敏,刘绚,周元刚.考虑极端事件下的高比例可再生能源电力系统韧性增强策略[J].电力系统自动化,2023,47(12):19-27.
DU Min,LIU Xuan,ZHOU Yuangang.Resilience Enhancement Strategy for Power System with High Proportion of Renewable Energy Considering Extreme Events[J].Automation of Electric Power Systems,2023,47(12):19-27.
杜敏,刘绚,周元刚.考虑极端事件下的高比例可再生能源电力系统韧性增强策略[J].电力系统自动化,2023,47(12):19-27. DOI: 10.7500/AEPS20220321019.
DU Min,LIU Xuan,ZHOU Yuangang.Resilience Enhancement Strategy for Power System with High Proportion of Renewable Energy Considering Extreme Events[J].Automation of Electric Power Systems,2023,47(12):19-27. DOI: 10.7500/AEPS20220321019.
近年来,极端事件与风电出力的不确定性给电力系统的安全运行带来了严峻挑战。文中提出一种考虑极端事件并以风电不确定性为导向的自适应鲁棒优化模型以增强电力系统的韧性能力。首先,考虑风电出力不确定性以构建自适应鲁棒多面体不确定性集合。其次,考虑极端事件对电力系统的威胁,提出了防御-攻击-防御框架下风电出力不确定性的电力系统韧性增强模型。最后,该模型在IEEE RTS-79和IEEE RTS-96测试系统上进行仿真验证,并采用列与约束生成算法进行求解,仿真结果验证了所提模型及求解方法的有效性。
In recent years
extreme events and uncertainty of wind power generation have brought serious challenges to the security operation of power systems. This paper proposes an adaptive robust optimization model to enhance the resilience of the power system considering wind power generation uncertainty under extreme events. Firstly
an adaptive robust polyhedral uncertainty set is constructed by considering the wind power generation uncertainty. Secondly
considering the threat of extreme events to the power system
a resilience enhancement model of power system considering wind power output uncertainty in the defense-attack-defense framework is proposed. Finally
the model is simulated and verified on the IEEE RTS-79 and IEEE RTS-96 test systems
which is solved by the column-and-constraint generation (C&CG) algorithm. The simulation results fully verified the effectiveness of the proposed model and solution method.
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