Integrating big data analytics and cybersecurity for power distribution networks with distributed energy resources

Abstract

The legacy electric power distribution system is designed primarily for unidirectional power flow from the electric grid made of large rotating electric machine-based generators located away from the load centers through highly interconnected transmission and sub-transmission network and radial distribution systems. The legacy distribution network is not designed to handle multiple sources of distributed energy resources (DER) such as different forms of photovoltaic (PV) systems, electric vehicles (EV), storage and wind power. However, the future grid is transitioning to system with bidirectional power flow at the distribution level with increasing penetration of DERs. DER penetration level is increasing drastically, in particular PV and storage, in distribution system and is expected to grow in excess of 50% within few decades. The monitoring and efficient control of such DERs requires data and communication that allows the integration of DERs with the modern grid. It also brings vulnerabilities for cyber-attacks that can have a negative impact on overall electric power system operation. In order to design a cost-effective communication system for a smart distribution system it is necessary to consider the cyber-physical relationships as well as the big data analytics and cybersecurity features of such design. Those aforementioned features should be included in the early stages of ICT design. In order to address the new challenges of ICT design for DERs this research studies different approaches on how to integrate big data analytics and cybersecurity to the traditional ICT design approaches. One of the major contributions of this research is the development of a highly detailed cyber-physical communication model platform done in Network Simulator 3 that can be used for simulations of advanced metering infrastructure (AMI). This simulation platform can be used to test and to validate new cybersecurity and data analytics tools of an information and communication technology design for smart distribution system. Other contributions include (a) a comprehensive study on big data analytics (BDA) for distributed energy resources, based on both extensive literature review and mathematical equations for analyzing the amount of data increase in observed data from power quality analysis at distribution level. (b) a set of cybersecurity recommendations at device level for improving the overall cybersecurity of distributed energy resources, based on the literature review together with the previous research done at the National Renewable Energy Laboratory (NREL).