In this work, we study coordination control and effective deployment of thyristor-controlled series compensation (TCSC) to protect power grids against disruptive disturbances. The power grid consists of flexible alternate current transmission systems (FACTS) devices for regulating power flow, phasor measurement units (PMUs) for detecting system states, and control station for generating the regulation signals. We propose a novel coordination control approach of TCSC devices to change branch impedance and regulate the power flow against unexpected disturbances on buses or branches. More significantly, a numerical method is developed to estimate a gradient vector for generating regulation signals of TCSC devices and reducing computational costs. To describe the degree of power system stress, a performance index is designed based on the error between the desired power flow and actual values. Moreover, technical analysis is presented to ensure the convergence of the proposed coordination control algorithm. Numerical simulations are implemented to substantiate that the coordination control approach can effectively alleviate the stress caused by contingencies on IEEE 24 bus system, as compared to the classic PID control. It is also demonstrated that the deployment of TCSCs can alleviate the system stress greatly by considering both impedance magnitude and active power on branches.
This paper addresses the distributed resilient filtering for discrete-time large-scale systems (LSSs) with energy constraints, where their information are collected by sensor networks with a same topology structure. As a typical model of information physics systems, LSSs have an inherent merit of modeling wide area power systems, automation processes and so forth. In this paper, two kinds of channels are employed to implement the information transmission in order to extend the service time of sensor nodes powered by energy-limited batteries. Specifically, the one has the merit of high reliability by sacrificing energy cost and the other reduces the energy cost but could result in packet loss. Furthermore, a communication scheduling matrix is introduced to govern the information transmission in these two kind of channels. In this scenario, a novel distributed filter is designed by fusing the compensated neighboring estimation. Then, two matrix-valued functions are derived to obtain the bounds of the covariance matrices of one-step prediction errors and the filtering errors. In what follows, the desired gain matrices are analytically designed to minimize the provided bounds with the help of the gradient-based approach and the mathematical induction. Furthermore, the effect on filtering performance from packet loss is profoundly discussed and it is claimed that the filtering performance becomes better when the probability of packet loss decreases. Finally, a simulation example on wide area power systems is exploited to check the usefulness of the designed distributed filter.