An approach for real-time tuning of cost functions in optimal System-Centric Wide Area Controller based on Adaptive Critic Design

This paper presents a method for real-time tuning of cost functions in coordinated wide area controller for improved power system transient stability. The algorithm is an optimal Wide Area System-Centric Controller and Observer (WASCCO) based on Adaptive Critic Design (ACD). ACD techniques using reinforcement learning (RL) are able to approximate dynamic programming based nonlinear optimal control but, the cost function for the optimal control requires online tuning. Here cost function defined in ACD are analyzed online with Lyapunov stability function. Further an online tuning method is designed based on eigenvalues extracted based on Prony analysis and linked to performance index generation. Results on a two area system shows better response compared to conventional schemes.