| 引用本文: | 周冬玥,胡福年,陈 军.基于复杂网络的电力系统鲁棒性分析[J].电力系统保护与控制,2021,49(1):72-80.[点击复制] |
| ZHOU Dongyue,HU Funian,CHEN Jun.Robustness analysis of power system based on a complex network[J].Power System Protection and Control,2021,49(1):72-80[点击复制] |
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| 摘要: |
| 随着电力系统在现代社会发展中的地位不断提高，其面临的各种危险也越来越引起人们的高度关注。为探究电力系统鲁棒性，建立了考虑电力系统实际运行机理的网络化模型。基于复杂网络理论，按照方法论原则，提出了一种鲁棒性分析方法。分别从结构和功能上给出了电力系统的鲁棒性分析指标，并模拟了电力系统三种故障情形。运用IEEE30测试网络，比较了基于复杂网络的分析方法与基于常规潮流分析的系统崩溃结果，对提出的分析框架进行了验证。同时，采取IEEE300网络和符合小世界特性及无标度特性的1 000节点网络模型对电力系统的鲁棒性进行了详细的分析。结果表明，该分析方法可以对多种情况的电力系统进行鲁棒性全面评估，证明了该方法的有效性。 |
| 关键词: 复杂网络 电力系统鲁棒性 故障模拟 网络特性 |
| DOI：DOI: 10.19783/j.cnki.pspc.200204 |
| 投稿时间：2020-03-03修订日期：2020-06-09 |
| 基金项目:国家自然科学基金项目资助(61773186) |
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| Robustness analysis of power system based on a complex network |
| ZHOU Dongyue,HU Funian,CHEN Jun |
| (Jiangsu Normal University, Xuzhou 221000, China) |
| Abstract: |
| Along with the continuous rise of the importance of power systems, the various dangers they face have attracted increasing attention. In order to explore the robustness of power systems, a networked model considering the actual operating mechanism of a power system is established. Based on complex network theory and a methodological principle, a robust analysis method is proposed. The robustness analysis indices of the power system are given in terms of structure and function, respectively, and three failure scenarios of the power system are simulated. Using the IEEE30 network, the analysis method based on the complex network is compared with the system collapse results based on the conventional power flow analysis, and the proposed analysis framework is verified. At the same time, the robustness of the power system is analyzed in detail using the IEEE300 network and the 1000-node network model that meets the characteristics of small world and scale-free characteristics. The results show that the analysis method can comprehensively evaluate the robustness of power systems in various situations, proving the effectiveness of the method.
This work is supported by National Natural Science Foundation of China (No. 61773186). |
| Key words: complex network power system robustness fault simulation network characteristics |
