Adaptive data-driven secondary control and cyberattack-resilient secondary control for AC microgrids

交流微电网的自适应数据驱动二次控制和抗网络攻击二次控制

• 批准号: 571554-2021
• 负责人: Wang, Xiaozhe
• 金额: $ 3.28万
• 依托单位: McGill University
• 依托单位国家: 加拿大
• 项目类别: Alliance Grants
• 财政年份: 2021
• 资助国家: 加拿大
• 起止时间: 2021-01-01 至 2022-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=729183
• 关键词: Adaptive; data; driven; secondary; control

More than 100 remote communities in Canada are not connected to the national electrical grid. They rely mainly on diesel for electricity, suffering from high costs and pollutions. Meanwhile, damage from snowstorms and wildfires becomes a leading cause of power outages in Canada. To increase the renewable energy supply and enhance the resiliency of electric power grids under extreme weather, microgrids, small-scale and self-sufficient energy systems, can play a crucial role. Compared to the bulk power systems, microgrids that can operate in both grid-connected and islanded modes have the advantages of low-carbon consumption and high self-healing capability. Despite many benefits, microgrids also bring new challenges. Microgrids dominated by the converter-interfaced distributed energy resources (DERs) are characterized with low inertia, meaning that microgrid voltage and frequency tend to experience large deviations subject to real-time power imbalance. Such deviations without timely correction may cause a severer power imbalance or even catastrophic system collapse. Secondary control is conceived as an effective means to correct the voltage and frequency deviations, which is conventionally carried out based on an apriori accurate physical model and intact sensor data. Nevertheless, an accurate physical model may not always be available due to diverse operating modes of converters and varying network topologies, while sensor data is susceptible to cyberattacks because of the vulnerability of information infrastructure. The plausibility of cyberattacks against the electric power sector is evident from the recent intrusion events, e.g., the penetration of a U.S. nuclear power plant near Burlington, Kansas, in 2017.To address these challenges, in this research project, we intend to develop novel adaptive secondary control and cyberattack-resilient secondary control for AC microgrids. Leveraging on Koopman operator theory, distributed control, and reinforcement learning, we will: 1). develop a novel online adaptive secondary control framework for microgrids to correct frequency and voltage deviations in real-time, without any prior knowledge of the grid model and warm-up training; 2). study the impacts of cross-layer cyberattacks on the developed secondary control methodologies; 3) design cyberattack-resilient secondary control methods using deep reinforcment learning techniques.Widespread power outages due to extreme weather or malicious cyberattacks are not only costly but also wreak havoc on millions of people's daily lives and profoundly disrupt the delivery of essential services (e.g., food, health care). The proposed research will yield novel cyberattack-resilient secondary control algorithms to ensure the stable operation of microgrids under varying grid topologies, working modes, and even under cyberattacks. The research outcomes will contribute to the advancement of developing secure and stable microgrids, the enhancement of reliable electric power, and the development of secure, clean, and resilient communities.

加拿大有100多个偏远社区与国家电网没有连接。他们主要依靠柴油来进行电力，遭受高昂的成本和污染。同时，暴风雪和野火的破坏成为加拿大停电的主要原因。为了增加可再生能源供应并在极端天气下提高电力网格的弹性，微电网，小规模和自给自足的能源系统可以发挥至关重要的作用。与散装功率系统相比，可以在网格连接和岛屿模式下运行的微电网具有低碳消耗和高自我修复能力的优势。尽管有很多好处，但微电网也带来了新的挑战。以低惯性为主导的微电网以相互交换的分布能资源（DER）为特征，这意味着微电网电压和频率倾向于经历大型偏差，但会受到实时功率不平衡的影响。这种没有及时校正的偏差可能会导致功率不平衡甚至灾难性系统崩溃。二级控制被认为是纠正电压和频率偏差的有效手段，该方法通常是根据Apriori精确的物理模型和完整的传感器数据进行的。 然而，由于转换器的不同操作模式和不同的网络拓扑模式，准确的物理模型可能并不总是可用的，而由于信息基础架构的脆弱性，传感器数据易受网络攻击。网络攻击对电力部门的合理性可以从最近的入侵事件中可以明显看出，例如，在2017年，美国核电站在堪萨斯州伯灵顿附近的美国核电站的穿透。为了解决这些挑战，在这项研究项目中，我们打算开发新型的适应性二级控制和Cyber​​AttaCk-Resberattack-Cyber​​Attact-cyberAttact-cyberAttack-Resilient二级控制，以实现AC微电网。利用Koopman操作员理论，分布式控制和强化学习，我们将：1）。为微电网建立一个新颖的在线自适应次级控制框架，以实时纠正频率和电压偏差，而无需任何先验网格模型和热身训练； 2）。研究跨层网络攻击对发达的二级控制方法的影响； 3）设计使用深钢筋学习技术的设计网络攻击二次控制方法。由于极端天气或恶意网络攻击而导致的遍布停电不仅代价高昂，而且对数百万人的日常生活造成了严重破坏，并严重破坏了必需服务的交付（例如，食品，食品，医疗保健）。拟议的研究将产生新型的网络攻击二级控制算法，以确保在不同的网格拓扑，工作模式甚至网络攻击下的微电网运行稳定。研究结果将有助于发展安全和稳定的微电网，可靠的电力增强以及安全，清洁和弹性的社区的发展。