| 引用本文: | 曹茂森,王蕾报,胡博,谢开贵,伏坚,温力力,周平,范璇,李博,曾意.考虑电-气耦合系统连锁故障的多阶段信息物理协同攻击策略[J].电力自动化设备,2019,39(8): |
| CAO Maosen,WANG Leibao,HU Bo,XIE Kaigui,FU Jian,WEN Lili,ZHOU Ping,FAN Xuan,LI Bo,ZENG Yi.Coordinated cyber-physical multi-stage attack strategy considering cascading failure of integrated electricity-natural gas system[J].Electric Power Automation Equipment,2019,39(8): |
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| 考虑电-气耦合系统连锁故障的多阶段信息物理协同攻击策略 |
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曹茂森1, 王蕾报1, 胡博1, 谢开贵1, 伏坚1, 温力力2, 周平2, 范璇2, 李博2, 曾意2
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1.重庆大学 输配电装备及系统安全与新技术国家重点实验室，重庆 400044;2.国网重庆市电力公司经济技术研究院，重庆 401120
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| 摘要: |
| 针对电-气耦合系统在恶意攻击下的风险分析，提出了一种计及电-气耦合系统连锁故障的信息物理多阶段协同攻击策略。为了诱导调度人员做出错误调度决策和降低电网的安全裕度，提出了一种以最大化线路过载程度为目标的改进负荷重分配(LR)攻击模型。综合考虑天然气系统与电力系统的调度时间尺度差异，构建一种新型的电-气耦合系统多阶段协同攻击策略：初始阶段通过攻击气网侧气源或管道以影响电-气耦合节点的天然气机组状态，然后针对电力系统交替采用改进LR攻击和物理攻击，最终导致大规模连锁停运。基于Q-Learning提出了最优策略求解算法，以比利时20节点天然气系统和IEEE 30节点系统为算例，验证了所提信息物理协同攻击模型的正确性和有效性。 |
| 关键词: 多能源系统 电-气耦合系统 负荷重分配攻击 信息物理协同攻击 连锁故障 Q-Learning算法 |
| DOI：10.16081/j.epae.201908041 |
| 分类号:TP393;TM71 |
| 基金项目:国家自然科学基金资助项目(51725701) |
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| Coordinated cyber-physical multi-stage attack strategy considering cascading failure of integrated electricity-natural gas system |
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CAO Maosen1, WANG Leibao1, HU Bo1, XIE Kaigui1, FU Jian1, WEN Lili2, ZHOU Ping2, FAN Xuan2, LI Bo2, ZENG Yi2
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1.State Key Laboratory of Power Transmission Equipment & System Security and New Technology, Chongqing University, Chongqing 400044, China;2.State Grid Chongqing Economic Research Institute, Chongqing 401120, China
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| Abstract: |
| As for the risk analysis of integrated electricity-natural gas system under malicious attack, the coordinated cyber-physical multi-stage attack strategy that takes into account the cascading failure of integrated electricity-natural gas system is proposed. Firstly, in order to mislead the operator and reduce the safety margin of power grid, an improved LR(Load Redistribution) attack model is proposed to maximize the degree of line overload. Secondly, considering the time-scale difference of dispatching between natural gas system and power system, a new coordinated multi-stage attack strategy for integrated electricity-natural gas system is constructed. In the initial stage, gas sources or pipelines in gas system are attacked to influence the state of natural gas generators at the integrated electricity-natural gas node. Then, the improved LR attack and physical attack are adopted alternately to the power system, which eventually leads to a blackout. Finally, a Q-Learning based algorithm is proposed to identify the optimal attack strategy. The correctness and validity of the proposed attack strategy are verified by the Belgium 20-node natural gas system and the IEEE 30-bus system. |
| Key words: multi-energy system integrated electricity-natural gas system load redistribution attack model coordinated cyber-physical attack cascading failure Q-Learning algorithm |
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