基于态势感知的电力系统抗信息攻击韧性研究

With the development of energy Internet, the integration process of information systems and industrial systems has been accelerated. At the same time, it has formed extensive interaction with human society. The modern power system is developing towards a "social-cyber-physical" With the development of energy Internet, the integration process of information systems and industrial systems has been accelerated. Meanwhile, human society is extensively interacted, and a "social-cyber-physical" complex symbiosis system is forming. Thus, cyber attacks will become one of the hidden threats to the security and stability of energy system. This subject intends to construct a cyber-attack analysis model, which integrates the attacker group, information system and power system, and study the resilience of the power system when suffered cyber attacks. Firstly, based on the social psychology analysis and large data analysis, the key inducing factors and characteristic factors of cyber attacks to power system is extracting respectively. Accordingly, the cyber-attack threating database is constructed, and the situation awareness of cyber attacks can be performed by the multi-source heterogeneous data sourced. Secondly, through the mapping relation of information flow, a "social-cyber-physical" fusion analysis model is constructed, which can show the path of attack fault diffusion. Finally, the framework of resilience evaluation of power system against cyber attack is proposed, and the robust optimization is applied to solve the resilience evaluation with given attacking behavior set. The results will provide technical support for accurate evaluation and control decision of the self-healing ability of the smart grid.

能源互联网的发展加快了信息系统与工业系统的融合进程，同时与人类社会形成了广泛互动，一个“社会-信息-物理”复杂共生系统正在逐渐形成，而信息攻击也将成为威胁能源系统安全稳定运行的重要隐患之一。本课题拟构建一个融合攻击者群体、信息系统、电力系统的信息攻击分析模型，对电力系统抗信息攻击的韧性进行研究。其一，应用社会心理学和大数据分析方法分别提取电力信息攻击的关键诱发要素和关键特征要素，构建电力信息攻击威胁库，并基于多源异构信息库进行攻击态势感知；其二，通过信息流映射关系构建“社会-信息-物理”融合分析模型，模拟攻击故障扩散的模式；其三，提出电力系统抗信息攻击的韧性评价体系，并应用鲁棒优化求解给定攻击态势集合条件下的电力系统抗信息攻击韧性评估问题。研究成果将为智能电网自愈能力的准确评价和安全控制决策提供技术依据。

能源互联网的发展加快了信息系统与工业系统的融合进程，同时与人类社会形成了广泛互动，一个“社会-信息-物理”复杂共生系统正在逐渐形成，而信息攻击也将成为威胁能源系统安全稳定运行的重要隐患之一。本项目构建了一个融合攻击者群体、信息系统、电力系统的信息攻击分析模型，对电力系统抗信息攻击的韧性进行研究。其一，应用社会心理学对具有不同攻击目的攻击者行为进行机理分析，并应用效用函数和大数据分析等方法提取电力信息攻击的关键诱发要素和关键特征要素，构建电力信息攻击威胁库，基于多源异构信息库进行攻击行为模拟和攻击态势感知，研究涵盖了虚假数据注入攻击及信息物理协同攻击等攻击模式；其二，通过信息流映射关系构建“社会-信息-物理”融合分析模型，模拟信息攻击行为发生后故障扩散的过程及后果，提出将不同类型信息扰动对信息系统的影响后果统一表征为信息网络拓扑、信息完整性和可用性的状态，进而构建同时考虑多类型信息扰动的电力系统可靠性评估框架体系；其三，提出电力系统抗信息攻击的韧性评价体系，将经典的韧性三角指标与场景概率相结合，定义韧性系统指标，包括：系统吸收率（灾害场景下系统能保持供电的负荷容量比例与灾害场景概率乘积之和）、系统适应率（故障场景下系统经过恢复措施所能达到的运行稳定状态比例与场景概率乘积之和）、系统修复速率（故障场景下系统能恢复到稳定状态的恢复速度与场景概率乘积之和）。研究成果能更有效地对电力系统信息安全威胁进行感知，并为高度信息化的新型电力系统安全可靠运行和规划建设提供决策依据。