Optimization Models for Advanced Cyber-security in the Smart Grid

Abstract

The power grid is increasingly dependent on information and communication technologies, which puts more emphasis on the importance of power system security as one of the top priorities. Internal and external factors can put the security of the power system at risk. The external factors include cyber-terrorist attacks, sabotage and environmental impacts while the internal factors are inherent to the accuracy of power system applications and their associated input data. As the utility industry becomes more automated and relies more on automated devices, the major threat to the grid is shifting from equipment failures to cyber-security attacks. Hence, improvement of the cyber-security of the power grid along with the reliability of the power system operations are primary focus of the United States government, power industry executives, and the research community.

Cyber-attacks to power systems could cause huge financial losses and substantial damages to the power grid. Hence, the main goal of the research summarized in this dissertation is to highlight the risks associated to the cyber-attacks to power systems and develop algorithms and models to improve the safe operations of the electric power grid. To achieve this goal, a detection algorithm is developed to avoid cyber-attacks to the optimal power flow (OPF) software module of the power systems. Since there is no guarantee that detection models detect all potential cyber-attacks, it is necessary to equip power systems with response models which avoid propagation of the cyber-atacks. In this dissertation, cyber-attacks to a specific network of the power systems, known as the phasor measurement unit (PMU) network, have been discussed, and a risk mitigation model for cyber-attacks to PMU networks is proposed. PMUs provide the system operators with the real-time operating status of the power grid, which can be further utilized for better cyber-security of the power grid. Since PMUs require considerable capital investments, an investment decision model is developed in this dissertation for the optimal allocation of phasor measurement units. Therefore, this dissertation outlines a research that will consider the OPF and state estimation modules of the electrical power systems and deliver the following outcomes. 1) An algorithm for real-time data reassurance in the OPF module 2) A probabilistic risk mitigation model for cyber-attacks to PMU networks 3) An investment decision model for the optimal allocation of phasor measurement units The remainder of this dissertation is organized as follows. Chapter 1 explains the cyber-security problem of the OPF module and introduces the real-time data reassurance model to improve the cyber-security of the OPF module. Chapter 2 provides background information about cyber-security of the PMU networks and explains the probabilistic risk mitigation model for cyber-attacks to the PMU networks. Chapter 3 discusses the challenges of the optimal placement of PMUs (OPP) problem and describes the developed investment decision model to allocate PMUs with minimum capital costs.