During the last two decades, distributed energy systems, especially renewable energy sources (RES), have become more economically viable with increasing market share and penetration levels on power systems. In addition to decarbonization and decentralization of energy systems, digitalization has also become very important. The use of artificial intelligence (AI), advanced optimization algorithms, Industrial Internet of Things (IIoT), and other digitalization frameworks makes modern power system assets more intelligent, while vulnerable to cybersecurity risks. This paper proposes the concept of the Internet of Predictable Things (IoPT) that incorporates advanced data analytics and machine learning methods to increase the resiliency of cyber-physical systems against cybersecurity risks. The proposed concept is demonstrated using a cyber-physical system testbed under a variety of cyber attack scenarios as a proof of concept (PoC).
翻译:在过去二十年中,分布式能源系统,特别是可再生能源,随着电力系统的市场份额和渗透水平的提高,在经济上更加可行。除了能源系统的去碳化和分散化之外,数字化也变得非常重要。使用人工智能(AI)、先进优化算法、工业信息互联网(IIoT)和其他数字化框架使现代电力系统资产更加智能,同时容易受到网络安全风险的影响。本文件提出了可预见事物互联网的概念,其中包括先进的数据分析学和机器学习方法,以提高网络物理系统抵御网络安全风险的能力。所提议概念的证明是利用在各种网络攻击情景下测试的网络物理系统作为概念的证明(POC )。