Abstract
This chapter presents a comprehensive review of the impacts of cyber attacks on the smart distribution grid and discusses the potential methods in the literature to mitigate them. The review considers different real-world case studies of successful cyber attacks on multiple grid assets, including networks with high-penetration of distributed energy resources (DERs). A specific use-case of a false data injection (FDI) attack on a photovoltaic (PV) production meter data used for 15-minute ahead forecasting is presented. The false data from the production meter causes the command and control center to give incorrect operational settings to the grid. The various impacts of this incorrect operational settings on the dynamics on the grid is theoretically analyzed, followed by simulation studies of this scenario on an IEEE 34 bus system with three PVs, one synchronous generator, and one energy storage. The impact of FDI on the system is analyzed by measuring the nodal voltages, the current flowing through the lines, and the systems’ active and reactive power losses. The results show that the FDI could potentially cause cascading failures due to possible over current and voltage collapse. This monograph also proposes an adaptive protection system based on a neural network model. This allows the network protection scheme to learn (based on the historical data) the dynamics of the system over time and adequately adapt the protection settings of the relays autonomously despite an FDI attack on the PV production meter. This study will be of particular importance to the utility and DER installers to proactively mitigate FDI attacks, thereby improving the overall situation awareness.
This work is funded by NSF under the grant numbers CNS-1553494 and CNS-1446570.
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Olowu, T.O., Dharmasena, S., Hernandez, A., Sarwat, A. (2021). Impact Analysis of Cyber Attacks on Smart Grid: A Review and Case Study. In: Tyagi, H., Chakraborty, P.R., Powar, S., Agarwal, A.K. (eds) New Research Directions in Solar Energy Technologies. Energy, Environment, and Sustainability. Springer, Singapore. https://doi.org/10.1007/978-981-16-0594-9_3
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