Resilient dynamic state estimation for multi-machine power system with partial missing measurements

Accurate tracking the dynamics of power system plays a significant role in its reliability, resilience and security. To achieve the reliable and precise estimation results, many advanced estimation methods have been developed. However, most of them are aiming at filtering the measurement noise, while the adverse affect of partial measurement missing is rarely taken into account. To deal with this issue, a discrete distribution in the interval [0,1] is introduced to depict mechanism of partial measurement data loss that caused by the sensor failure. Then, a resilient fault tolerant extended Kalman filter (FTEKF) is designed in the recursive filter framework. Eventually, extensive simulations are carried on the different scale test systems. Numerical experimental results illustrate that the resilience and robustness of the proposed fault tolerant EKF method against partial measurement data loss

Resilient dynamic state estimation for power system using Cauchy-kernel-based maximum correntropy cubature Kalman filter

Accurate estimation of dynamic states is the key to monitoring power system operating conditions and controlling transient stability. The inevitable non-Gaussian noise and randomly occurring denial-of-service (DoS) attacks may, however, deteriorate the performance of standard filters seriously. To deal with these issues, a novel resilient cubature Kalman filter based on the Cauchy kernel maximum correntropy (CKMC) optimal criterion approach (termed CKMC-CKF) is developed, in which the Cauchy kernel function is used to describe the distance between vectors. Specifically, the errors of state and measurement in the cost function are unified by a statistical linearization technique, and the optimal estimated state is acquired by the fixed-point iteration method. Because of the salient thick-tailed feature and the insensitivity to the kernel bandwidth (KB) of Cauchy kernel function, the proposed CKMC-CKF can effectively mitigate the adverse effect of non-Gaussian noise and DoS attacks with better numerical stability. Finally, the efficacy of the proposed method is demonstrated on the standard IEEE 39-bus system under various abnormal conditions. Compared with standard cubature Kalman filter (CKF) and maximum correntropy criterion CKF (MCC-CKF), the proposed algorithm reveals better estimation accuracy and stronger resilience

Real-time digital simulation of switching power circuits

grantor: University of TorontoSophisticated power electronic apparatus and their digital control systems are finding increasing applications in electric power systems at generation, transmission, distribution and utilization levels. It is essential to carry out rigorous performance evaluation of the power electronic equipment and their digital controllers prior to their commissioning on the host power system. The current trend to achieve that goal is to interface a real-time digital simulator representing the power electronic apparatus and the host power system with the digital controller. This thesis addresses the issue of synchronization between the output signals of the digital controller for firing power electronic switches and the discrete time-step of the real-time simulator. It is shown that lack of such synchronization can lead to severe inaccuracies in the simulation results. A novel real-time simulation algorithm is proposed for accounting incoming switching events in fixed step-size digital simulation. This algorithm relies on the registration of the timing of the switching events and a subsequent correction procedure to calculate the system state. Off-line time domain simulations of a Pulse Width Modulated (PWM) Voltage Source Inverter (VSI) system demonstrate a ten-fold improvement in accuracy of the proposed algorithm over the fixed step-size algorithm using the same step-size. Practical feasibility of the proposed algorithm is demonstrated by implementation on a digital computing platform comprising of a DSP and a FPGA. The hardware and software design process follows a modular approach which makes it amenable for implementation on next generation processors. A 5kVA experimental set-up of the PWM VSC system is used to verify the results of the real-time simulation.Ph.D

Exploring Gaussian elimination based solution methods of electric systems using circuit principles

Abstract In power system simulation, the mathematical solution methods are typically regarded as pure numerical operations, which are independent of the circuit principles. In this letter, it is demonstrated that the computational procedures in the commonly used numerical solution methods for circuit equations are essentially equivalent to the basic principles of electricity. The computational procedures of the representative Gaussian elimination based solution methods (including GE and pivoting method for sparsity of GE/LU) are comprehensively analyzed and their deep relationships with the circuit principles are revealed: the computation process of these mathematics based numerical solution methods can be completely explained using circuit principles. The interesting findings could help understand the computational process of solution methods from the circuit perspective, which may also guide the design of new circuit solution methods