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1. 清华大学电机工程与应用电子技术系, 北京市 100084
2. 电力系统及发电设备控制和仿真国家重点实验室,清华大学, 北京市 100084
3. 国网江苏省电力有限公司, 江苏省 南京市 210024
张至美(1993—),男,博士研究生,主要研究方向:电力系统安全性分析。E-mail: zzm16@mails.tsinghua.edu.cn
黄少伟(1985—),男,通信作者,博士,副研究员,主要研究方向:电力系统建模与仿真、电力系统并行和分布式计算、连锁故障、复杂网络理论与大电网安全、人工智能等。E-mail: huangsw@tsinghua.edu.cn
梅生伟(1964—),男,教授,博士生导师,主要研究方向:电力系统运行与控制、连锁故障、工程博弈论、大规模储能技术等。E-mail: meishengwei@tsinghua.edu.cn
收稿日期:2019-06-25,
修回日期:2019-09-06,
网络出版日期:2020-02-09,
纸质出版日期:2020-03-25
移动端阅览
张至美,黄少伟,梅生伟等.基于合作博弈的电网支路脆弱性评估方法[J].电力系统自动化,2020,44(06):9-16.
ZHANG Zhimei,HUANG Shaowei,MEI Shengwei,et al.Vulnerability Assessment Method of Branch Lines in Power Grid Based on Cooperative Game[J].Automation of Electric Power Systems,2020,44(06):9-16.
张至美,黄少伟,梅生伟等.基于合作博弈的电网支路脆弱性评估方法[J].电力系统自动化,2020,44(06):9-16. DOI: 10.7500/AEPS20190626005.
ZHANG Zhimei,HUANG Shaowei,MEI Shengwei,et al.Vulnerability Assessment Method of Branch Lines in Power Grid Based on Cooperative Game[J].Automation of Electric Power Systems,2020,44(06):9-16. DOI: 10.7500/AEPS20190626005.
电网支路脆弱性评估是连锁故障分析和防治的重要步骤。现有的脆弱性指标存在物理意义不明、未充分考虑多重故障对脆弱性的影响等问题。为此,首先构建电网支路的合作博弈框架,根据博弈结果将故障链的后果合理分配到每个支路,并以此作为电网支路的脆弱性指标。该指标能反映电网支路故障对停电事故导致电网损失的贡献,物理意义明确。为解决多重故障链的损失不满足超可加性的问题,将合作博弈的多目标优化问题转换为集体理性与个体理性2个阶段的优化模型,并分别使用遗传算法、线性规划求解。IEEE 39节点系统的算例分析验证了该指标的合理性。
The vulnerability assessment of branch lines in power grid is an important step in the subsequent analysis and prevention of cascading outages. Existing vulnerability indices have problems including unclear physical meaning
lacking consideration of the impact of multiple outages on vulnerability and so on. To address the issues
this paper constructs a cooperative game framework of branch lines in power grid. According to the game result
the loss caused by a fault chain is properly distributed to each branch line as their vulnerabilities. The indices can reflect the contribution of the fault on branch lines to the power grid loss caused by the outage accidents
and its physical meaning is clear. To solve the problem of the non-superposition of the loss of mutiple fault chains
the corresponding multi-objective optimal programming is transformed into a two-stage optimization model with collective rationality and individual rationality. The two-stage optimization model uses genetic algorithm and linear programming
respectively. The case study of IEEE 39-bus system verifies the validity of the proposed index.
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