A Multi-Agent System-Based Intelligent Heuristic Optimal Control System for A Large-Scale Power Plant

A large-scale power system is required to have a new control system to operate at a higher level of automation, flexibility, robustness, and optimization. In this paper, a multi-agent system based intelligent heuristic optimal control system (MAS-IHOCS) is presented for reference governor and optimal feedforward and feedback controls that improve the performance of the plant in a wide-range of operation. With the proposed architecture of a single agent and an organization of the multi-agent system, the MAS-IHOCS realizes the reference governor for generating optimal set-points and feedforward control actions by using particle swarm optimization (PSO). It also realizes feedback control actions which utilize optimal PI control gains obtained by using a differential evolutionary (DE) algorithm. The proposed MAS-IHOCS is a functional group in a multi-agent system-based intelligent control (MAS-IC), which has several functional groups that provide efficient ways to control locally and globally, and to accommodate and overcome the complexity of large-scale distributed systems.