Applying an intelligence-based adaptive multi-predictive control strategy to a two-area interconnected power system

Abstract

We look at a number of research works in the area of power system control to propose a novel strategy in line with the integration of intelligence-based techniques and also the adaptive multi-predictive control. In the strategy presented here, first of all, the one-area power system is represented, through sufficient mathematical relations, and subsequently the investigated outcomes are generalized to represent the two-area interconnected power system. Based on the proposed control strategy, namely IAMPCS in this investigation, the operating points of the two-area interconnected power system need to be represented through several linear models, where the best model of the system is accurately identified by an intelligent decision-maker mechanism at each instant of time. Hereinafter, an adaptive algorithm is instantly implemented on the chosen model to be efficient in the system representation and on the corresponding predictive control strategy, as well. In order to demonstrate the effectiveness of the proposed IAMPCS, the whole of simulation programs are carried out and the results are compared with those obtained using the single-model linear generalized predictive control, as well as the extended PI control schemes, as the benchmark one. The results verify the validity of the proposed control strategy in comparison with the previous approaches.