Cascading Failures and Contingency Analysis for Smart Grid Security

The modern electric power grid has become highly integrated in order to increase the reliability of power transmission from the generating units to end consumers. In addition, today’s power system are facing a rising appeal for the upgrade to a highly intelligent generation of electricity networks commonly known as Smart Grid. However, the growing integration of power system with communication network also brings increasing challenges to the security of modern power grid from both physical and cyber space. Malicious attackers can take advantage of the increased access to the monitoring and control of the system and exploit some of the inherent structural vulnerability of power grids. Therefore, determining the most vulnerable components (e.g., buses or generators or transmission lines) is critically important for power grid defense. This dissertation introduces three different approaches to enhance the security of the smart grid. Motivated by the security challenges of the smart grid, the first goal of this thesis is to facilitate the understanding of cascading failure and blackouts triggered by multi-component attacks, and to support the decision making in the protection of a reliable and secure smart grid. In this work, a new definition of load is proposed by taking power flow into consideration in comparison with the load definition based on degree or network connectivity. Unsupervised learning techniques (e.g., K-means algorithm and self-organizing map (SOM)) are introduced to find the vulnerable nodes and performance comparison is done with traditional load based attack strategy. Second, an electrical distance approach is introduced to find the vulnerable branches during contingencies. A new network structure different than the original topological structure is formed based on impedance matrix which is referred as electrical structure. This structure is pruned to make it size compatible with the topological structure and the common branches between the two different structures are observed during contingency analysis experiments. Simulation results for single and multiple contingencies have been reported and the violation of line limits during single and multiple outages are observed for vulnerability analysis. Finally, a cyber-physical power system (CPS) testbed is introduced as an accurate cyber-physical environment in order to observe the system behavior during malicious attacks and different disturbance scenarios. The application areas and architecture of proposed CPS testbed have been discussed in details. The testbed’s efficacy is then evaluated by conducting real-time cyber attacks and exploring the impact in a physical system. The possible mitigation strategies are suggested for defense against the attack and protect the system from being unstable

High Order Contingency Selection using Particle Swarm Optimization and Tabu Search

There is a growing interest in investigating the high order contingency events that may result in large blackouts, which have been a great concern for power grid secure operation. The actual number of high order contingency is too huge for operators and planner to apply a brute-force enumerative analysis. This thesis presents a heuristic searching method based on particle swarm optimization (PSO) and tabu search to select severe high order contingencies. The original PSO algorithm gives an intelligent strategy to search the feasible solution space, but tends to find the best solution only. The proposed method combines the original PSO with tabu search such that a number of top candidates will be identified. This fits the need of high order contingency screening, which can be eventually the input to many other more complicate security analyses. Reordering of branches of test system based on severity of N-1 contingencies is applied as a pre-processing to increase the convergence properties and efficiency of the algorithm. With this reordering approach, many critical high order contingencies are located in a small area in the whole searching space. Therefore, the proposed algorithm tends to concentrate in searching this area such that the number of critical branch combinations searched will increase. Therefore, the speedup ratio is found to increase significantly. The proposed algorithm is tested for N-2 and N-3 contingencies using two test systems modified from the IEEE 118-bus and 30-bus systems. Variation of inertia weight, learning factors, and number of particles is tested and the range of values more suitable for this specific algorithm is suggested. Although illustrated and tested with N-2 and N-3 contingency analysis, the proposed algorithm can be extended to even higher order contingencies but visualization will be difficult because of the increase in the problem dimensions corresponding to the order of contingencies

Improved fault-tolerant PMU placement using algebraic connectivity of graphs

Due to perpetual and innovative technological advancements, the need for reliable and stable power generation and transmission has been increasing dramatically over the years. Smart grids use advanced technologies to provide self-monitoring, self-checking and self-healing power networks, including smart metering devices capable of providing accurate measurements of the network’s power components. Among the most important metering devices in this context are “Phasor Measurement Units (PMUs)â€. PMUs are metering devices that provide synchronized measurements of voltage, current and phase angle differences using signals from the GPS satellites. However, due to the high cost of such advanced metering devices, studies were performed to determine the minimum number of PMUs required and their strategic placements in the power networks to provide full system observability. In this thesis, we consider fault-tolerant PMU placement aiming to minimize the number of PMUs while maintaining system observability under various contingencies. Conventionally, the optimal number of PMUs in a system is determined based on the system’s connectivity matrix under no contingency. This thesis considers fault- tolerant PMU placement under single and double branch failures. We propose algebraic connectivity, or Fiedler value, to identify the worst- case branch failures in terms of connectivity degradation. The proposed PMU placement accounts for this worst-case and covers a large percentage of other single and double branch failures. Furthermore, we propose the usage of Fiedler vector to provide a PMU placement that would ensure that the system remains fully observable during system partitioning into separate sub-systems. The resulting placements are compared with those obtained without considering connectivity degradation or system partitioning in terms of the percentages of observable systems during any single and double branch failures. The proposed PMU placements have increased percentages of fully observable systems in the event of any single or double branch failures compared to non—contingency based placement, with a reasonable increase in number of PMUs, and for some placement approaches no increase in PMUs is needed for providing a higher percentage of fully observable systems

Improved fault-tolerant PMU placement using algebraic connectivity of graphs

Due to perpetual and innovative technological advancements, the need for reliable and stable power generation and transmission has been increasing dramatically over the years. Smart grids use advanced technologies to provide self-monitoring, self-checking and self-healing power networks, including smart metering devices capable of providing accurate measurements of the network\u27s power components. Among the most important metering devices in this context are Phasor Measurement Units (PMUs) . PMUs are metering devices that provide synchronized measurements of voltage, current and phase angle differences using signals from the GPS satellites. However, due to the high cost of such advanced metering devices, studies were performed to determine the minimum number of PMUs required and their strategic placements in the power networks to provide full system observability. In this thesis, we consider fault-tolerant PMU placement aiming to minimize the number of PMUs while maintaining system observability under various contingencies. Conventionally, the optimal number of PMUs in a system is determined based on the system\u27s connectivity matrix under no contingency. This thesis considers fault- tolerant PMU placement under single and double branch failures. We propose algebraic connectivity, or Fiedler value, to identify the worst- case branch failures in terms of connectivity degradation. The proposed PMU placement accounts for this worst-case and covers a large percentage of other single and double branch failures. Furthermore, we propose the usage of Fiedler vector to provide a PMU placement that would ensure that the system remains fully observable during system partitioning into separate sub-systems. The resulting placements are compared with those obtained without considering connectivity degradation or system partitioning in terms of the percentages of observable systems during any single and double branch failures. The proposed PMU placements have increased percentages of fully observable systems in the event of any single or double branch failures compared to non—contingency based placement, with a reasonable increase in number of PMUs, and for some placement approaches no increase in PMUs is needed for providing a higher percentage of fully observable systems

Optimization Methods Applied to Power Systems Ⅱ

Electrical power systems are complex networks that include a set of electrical components that allow distributing the electricity generated in the conventional and renewable power plants to distribution systems so it can be received by final consumers (businesses and homes). In practice, power system management requires solving different design, operation, and control problems. Bearing in mind that computers are used to solve these complex optimization problems, this book includes some recent contributions to this field that cover a large variety of problems. More specifically, the book includes contributions about topics such as controllers for the frequency response of microgrids, post-contingency overflow analysis, line overloads after line and generation contingences, power quality disturbances, earthing system touch voltages, security-constrained optimal power flow, voltage regulation planning, intermittent generation in power systems, location of partial discharge source in gas-insulated switchgear, electric vehicle charging stations, optimal power flow with photovoltaic generation, hydroelectric plant location selection, cold-thermal-electric integrated energy systems, high-efficiency resonant devices for microwave power generation, security-constrained unit commitment, and economic dispatch problems