Emerging applications of IoT and cybersecurity for electrical power systems

摘要

With the growth of Internet of Things (IoT) techniques, applications have become smarter, and linked gadgets allow them to be used in many parts of power systems. Meanwhile, cybersecurity is used to improve an application's intelligence and capabilities, especially with the growing size of collected data. Further, the robustness of cybersecurity infrastructure can protect the risk of cyberattacks and facing systems from hackers. This fast-rising trend of IoT and cybersecurity has begun to grow worldwide, especially for power system applications. It is therefore worthwhile to present a comprehensive overview of the current actions and trends involving relative regulations and reservations towards power systems. In this regard, many academics have been drawn to the area of power systems, which have been explored using both Artificial Intelligence (AI) techniques and machine learning (ML) techniques, as well as IoT methodologies. Accordingly, this Special Issue seeks to encourage researchers to showcase cutting-edge research results in the field of promising applications of IoT and cybersecurity based on AI and ML techniques for power systems. This Special Issue contains a collection of high-quality research that focuses on important topics and offers valuable insights into modern electric power and energy sectors which are the implementation of IoT and Cybersecurity into numerous applications of electrical power systems. In this Special Issue, the Guest Editors have acknowledged a total of 17 papers which have all been sent to peer-review. Of these 17 papers, 8 have been accepted. These 8 papers were of a very good quality and have contributed to the success of the Special Issue; otherwise,9 papers have been rejected or referred to other journals. The papers address the following key areas: ‘Applications of IoT and digital twin in electrical power systems: A comprehensive survey’: This research paper reviews the applications of the Internet of Things (IoT) and digital twin technology in electrical power systems. It begins by discussing the generalized IoT value chain, followed by the terminology of smart grid, with clarifying the role of IoT-systems and the digital twin structure within the Smart Grid. A comparison between different short-range and long-range transports is presented. The paper then discusses the use of IoT and digital twin technology for effective energy management with applications in smart homes, smart buildings, smart grids, smart industries (Industry 4.0), smart transportation, and smart cities. Additionally, the paper explores the use of IoT and digital twin technology for condition monitoring and diagnosis (CMD) in electrical power systems. Three different cases are presented for CMD, that is, CMD of power transformers, CMD of electrical grids, and CMD of substations. IoT and digital twin applications are also highlighted in power electronic systems. Finally, the paper discusses the challenges and opportunities of applying IoT and digital twin technology to electrical power systems and provides recommendations for future research. ‘A rapid state estimation method for calculating transmission capacity despite cyber security concerns’: This research paper simulates cyberattacks in DIgSILENT for energy management and state estimation. Assuming hackers have adequate information to alter input data, they can alter the power market and the available transmission capability (ATC). Detection programs may fail if false information is coordinated in the presence of error information. The minimum number of network measurements before the state estimation program converges is 54% of the total measurements. In the new method, weighted least squares improve the state estimation speed. The new method can also improve the speed of ATC. In addition to identifying the cyberattack, the algorithm in the present paper can be used to identify the target of the attack. It also uses complete and correct information and even incor