Hybrid energy function based real-time optimal wide-area transient stability controller for power system stability

Abstract

This paper presents a hybrid direct and intelligent method of real-time coordinated wide-area controller for improved power system transient stability. The algorithm is applied as an optimal Wide-Area System-Centric Controller and Observer (WASCCO) based on Adaptive Critic Design (ACD). ACD techniques that uses Reinforcement Learning (RL) could be utilized to approximate the transient energy function by dynamic programming and find the solution to nonlinear optimal control problem. However, such technique is highly dependent on the cost function and its dynamics. A Lyupanov-based energy function that is defined offline and updated in real-time through prony analysis is utilized for this purpose. Results on a two area power system and 68-bus New England New York system shows better response compared to conventional schemes and local power system stabilizers.