Cloud-Based Dynamic Line Rating: Architecture, Services, and Cyber Security

Introduction

Advanced information and communication technologies (ICT) such as cloud computing, Internet of Things (IoT), big data, mobile Internet are gradually being deployed in the industrial sector. In the power industry, such a trend is continuing toward smart grids, Industrial IoT (IIoT) and the Internet of Energy (IoE). These new technologies should be used in production, transmission and distribution of electric power, thus constituting an intelligent electric power system (Zhou, Yang, & Shao, 2016).

Most of countries have experienced restructuring of their electric utility companies, due to the liberalization of the electricity market, as well as the rapid and continuous development of technologies for production of electric energy. Probably, the most significant changes relate to the use of distributed and renewable energy sources (Vezzoli et al., 2018, pp. 23-39). These processes caused an increase in electricity trading on the energy commodities exchange. The deregulated energy market forced fundamental changes in the investment and operational decisions regarding transmission lines. All these facts have strongly influenced the research, development and implementation of Dynamic Line Rating (DLR) systems.

Introduction of the DLR concept allows for a real-time control of the transmission line, based on the continuous evaluation of the actual thermal and other operating conditions, and further estimation of the acceptable transmission line's load and other relevant parameters that determine operational limitations. DLR systems detect additional available capacities and, in this way, provide advantageous conditions for power system management procedures.

DLR system can be implemented as a stand-alone solution, but it is commonly integrated with the power utility's Supervisory Control And Data Acquisition (SCADA) system (Bostjancic Rakas, Timcenko, A. Kabovic, & M. Kabovic, 2016; Uski-Joutsenvuo & Pasonen, 2013). Information obtained from the DLR system can further be processed by the utility Energy Management System (EMS) or Distribution Management System (DMS).

DLR systems perform continuous data acquisition and analysis and based on that provide energy optimization, prevention from the conductor overheating, and enhance the overall security and reliability of the power system. Since DLR operation relies strongly on receiving accurate data in real time, the information security is of the most importance and should be implemented with special care. Actually, implementation of the DLR system requires a proper level of information and network infrastructure security. Some recent initiatives were raised towards the proper and full assessment of the DLR data application in the operating environment (Federal Energy Regulatory Commission [FERC], 2019; U.S. Department of Energy, 2019). These reports define and analyze the impact of DLR systems on the availability of transmission line capacity, the optimization and accuracy in the process of the DLR protocol implementation, interoperability and cyber security capabilities, as well as the financial and environmental impacts.

DLR plays an important role in implementing the smart grids in the transmission network, thus allowing for prompt response in the case of detected incidents (Budka, Deshpande, & Thottan, 2014, pp. 209-225; National Association of State Energy Officials [NASEO], 2011). Cloud computing is a prospective model for support of smart grid applications due to its advanced computing and data storage capabilities, flexibility, provision for big data analytics, as well as cost savings (Dileep, 2020; Markovic, Zivkovic, Branovic, Popovic, & Cvetkovic, 2013). At the same time, cloud computing brings in some risks, primary in terms of security and reliability (Yigit, Gungor, & Baktir, 2014).

The objectives of this chapter are: (1) to provide a survey of technical capabilities for implementing DLR systems using cloud computing services and (2) to assess advantages and disadvantages of cloud-based DLR solutions with particular focus on cyber security, as a main risk factor.