This paper presents a security-constrained unit commitment (SCUC) algorithm which takes into account the intermittency and volatility of wind power generation. The UC problem is solved in the master problem with the forecasted intermittent wind power generation. Next, possible scenarios are simulated for representing the wind power volatility. The initial dispatch is checked in the subproblem and generation redispatch is considered for satisfying the hourly volatility of wind power in simulated scenarios. If the redispatch fails to mitigate violations, Benders cuts are created and added to the master problem to revise the commitment solution. The iterative process between the commitment problem and the feasibility check subproblem will continue until simulated wind power scenarios can be accommodated by redispatch. Numerical simulations indicate the effectiveness of the proposed SCUC algorithm for managing the security of power system operation by taking into account the intermittency and volatility of wind power generation.

State estimation is a key element in today's power systems for reliable system operation and control. State estimation collects information from a large number of meter measurements and analyzes it in a centralized manner at the control center. Existing state estimation approaches were traditionally assumed to be able to tolerate and detect random bad measurements. They were, however, recently shown to be vulnerable to intentional false data injection attacks. This paper fully develops the concept of load redistribution (LR) attacks, a special type of false data injection attacks, and analyzes their damage to power system operation in different time steps with different attacking resource limitations. Based on damaging effect analysis, we differentiate two attacking goals from the adversary's perspective, i.e., immediate attacking goal and delayed attacking goal. For the immediate attacking goal, this paper identifies the most damaging LR attack through a max-min attacker-defender model. Then, the criterion of determining effective protection strategies is explained. The effectiveness of the proposed model is tested on a 14-bus system. To the author's best knowledge, this is the first work of its kind, which quantitatively analyzes the damage of the false data injection attacks to power system operation and security. Our analysis hence provides an in-depth insight on effective attack prevention with limited protection resource budget.

With an increasing number of distributed energy resources (DERs) integrated to the power system, inverters need to take corresponding responsibility for the security and stability of the system. Virtual synchronous generators (VSGs) are proposed to mimic dynamic characteristics of traditional rotational synchronous generators (RSGs) to compensate for the loss of inertia and reserve capacity. Similar to RSGs, VSGs will experience transient angle instability under certain conditions, which probably threatens the system security. In this paper, transient angle stability of a VSG is investigated by Lyapunov’s direct method. The deteriorative effect of reactive power control loop on transient angle stability is first analyzed and then voltage variation is incorporated into an approximate Lyapunov’s direct method. In this method, the inverter internal voltage is treated as a parameter rather than a state variable. Moreover, the influence of different parameters on transient angle stability is studied. Finally, an enhanced control strategy is presented to improve the transient angle stability by adjusting the reference power. Numerical simulation results are presented to validate the effectiveness of the proposed method and the enhanced control.

The contribution of this paper focuses on the development of a security-based methodology for the solution of short-term SCUC when considering the impact of natural gas transmission system. The proposed methodology examines the interdependency of electricity and natural gas in a highly complex transmission system. The natural gas transmission system is modeled as a set of nonlinear equations. The proposed solution applies a decomposition method to separate the natural gas transmission feasibility check subproblem and the power transmission feasibility check subproblem from the hourly unit commitment (UC) in the master problem. Gas contracts are modeled and incorporated in the master UC problem. The natural gas transmission subproblem checks the feasibility of natural gas transmission as well as natural gas transmission security constraints for the commitment and dispatch of gas-fired generating units. If any natural gas transmission violations arise, corresponding energy constraints will be formed and added to the master problem for solving the next iteration of UC. The iterative process will continue until a converged feasible gas transmission solution is found. A six-bus power system with seven-node gas transmission system and the IEEE 118-bus power system with 14-node gas transmission system are analyzed to show the effectiveness of the proposed solution. The proposed model can be used by a vertically integrated utility or the ISO for the short-term commitment and dispatch of generating units with natural gas transmission constraints.

This paper compares applications of scenario-based and interval optimization approaches to stochastic security-constrained unit commitment (Stochastic SCUC). The uncertainty of wind power generation is considered in this study to compare the two approaches, while other types of uncertainty can be addressed similarly. For the simulation of uncertainty, the scenario-based approach considers the Monte Carlo (MC) method, while lower and upper bounds are adopted in the interval optimization. The Stochastic SCUC problem is formulated as a mixed-integer linear programming (MIP) problem and solved using the two approaches. The scenario-based solutions are insensitive to the number of scenarios, but present additional computation burdens. The interval optimization solution requires less computation and automatically generates lower and upper bounds for the operation cost and generation dispatch, but its optimal solution is very sensitive to the uncertainty interval. The numerical results on a six-bus system and the modified IEEE 118-bus system show the attributes of the two approaches for solving the Stochastic SCUC problem. Several convergence acceleration options are also discussed for overcoming the computation obstacles in the scenario-based approach.

Power grid is one of the most critical infrastructures in a nation and could suffer a variety of cyber attacks. Recent studies have shown that an attacker can inject pre-determined false data into smart meters such that it can pass the residue test of conventional state estimator. However, the calculation of the false data vector relies on the network (topology and parameter) information of the entire grid. In practice, it is impossible for an attacker to obtain all network information of a power grid. Unfortunately, this does not make power systems immune to false data injection attacks. In this paper, we propose a local load redistribution attacking model based on incomplete network information and show that an attacker only needs to obtain the network information of the local attacking region to inject false data into smart meters in the local region without being detected by the state estimator. Simulations on the modified IEEE 14-bus system demonstrate the correctness and effectiveness of the proposed model. The results of this paper reveal the mechanism of local false data injection attacks and highlight the importance and complexity of defending power systems against false data injection attacks.