| 引用本文: | 赵晓龙,方恒福,王 罡,等.面向弹性配电网防灾减灾的组件重要度评估方法[J].电力系统保护与控制,2020,48(16):28-36.[点击复制] |
| ZHAO Xiaolong,FANG Hengfu,WANG Gang,et al.Component importance indices evaluation considering disaster prevention and mitigation in resilient distribution systems[J].Power System Protection and Control,2020,48(16):28-36[点击复制] |
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| 摘要: |
| 极端灾害事件日益频发，电力系统在小概率、大影响灾害事件下的弹性指标受到学术界、工业界的广泛关注。无论在灾害前的组件加固策略或者灾害期间的组件抢修策略中，若能够考虑灾害特性、系统运行等因素，动态辨识对配电网弹性提升更为有效的关键组件，将大大提高配电网防灾减灾的能力。面向弹性配电网防灾减灾，提出组件重要度评价指标与评估方法。首先，基于比例风险模型建立考虑天气、老化等因素影响的故障率模型，基于逆变换采样法生成灾害故障场景。其次，在每个场景中，假设组件i始终在线、始终离线两种情形，分别计算配电网弹性恢复最优方案。然后，对比两种恢复方案下系统弹性变化，评估组件i重要度指标。最后，建立收敛条件以保证评估精度。算例验证了评估指标与评估方法的有效性。 |
| 关键词: 弹性配电网 组件重要度 比例风险模型 蒙特卡罗 |
| DOI：DOI: 10.19783/j.cnki.pspc.191025 |
| 投稿时间：2019-08-25修订日期：2020-03-09 |
| 基金项目:国家电网公司总部科技项目资助(PDB172018 00056)“雄安新区高可靠配电网关键技术研究” |
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| Component importance indices evaluation considering disaster prevention and mitigation in resilient distribution systems |
| ZHAO Xiaolong,FANG Hengfu,WANG Gang,YANG Honglei,SUN Chenjun,SUN Chenjun |
| (1. China Electric Power Research Institute Co., Ltd., Beijing 100192, China; 2. Xiong’an New Area Power Supply Co.,
State Grid Hebei Electric Power Co., Ltd., Baoding 071800, China; 3. State Grid Hebei Electric Power Co., Ltd.,
Shijiazhuang 050022, China; 4. China Agricultural University, Beijing 100083, China) |
| Abstract: |
| Since extreme disasters become more frequent with climate change, resilience indices of power systems having low probability but large impact events gains increasing attention in both academia and industry. Either in the component hardening strategy before disaster or the rush repair strategy during disaster, disaster prevention and mitigation of distribution systems will be greatly improved if critical components can be identified dynamically especially for disaster characteristics and operational condition. This paper proposes component importance indices and evaluation methods for disaster prevention and mitigation in distribution systems. First, the proportional hazard model is introduced to model failure rate where influencing factors, such as aging condition and external weather condition, are considered. The inverse sampling method is introduced to generate outage scenarios. Then the paper assumes the status of component i online and offline in each scenario to calculate corresponding resilience restoration decisions. The importance indices of i based on the resilience difference between the two restoration decisions are evaluated. Finally, the convergence criterion is established to ensure accuracy. The rationality and effectiveness of the proposed indices and method are verified in case studies.
This work is supported by Science and Technology Project of the Headquarter of State Grid Corporation of China (No. PDB17201800056). |
| Key words: resilient distribution systems component importance proportional hazard model Monte Carlo |
