A multi-objective model for transmission network restoration based on multi-agent and Tabu Search

As power system restoration (PSR) is a multi-variable, multi-objective, and multi-constrained nonlinear optimization problem, it is difficult to establish a well-defined mathematical model to reasonably describe it. Given this background, a new distributed model for PSR is proposed in this paper by combining multi-agent technology (MAT) with tabu search method (TSM). The proposed model consists of a number of Crunode intelligent agents (CIAGs) and a single intelligent control agent (ICAG). These agents are co-operative and capable of interacting with each other dynamically to gain local optimal solutions. Based on that, TSM is utilized by ICAG to search for a global optimal solution. Through flexible interaction of agents and heuristic search of TSM, the optimal solution of PSR could be obtained and this is verified by simulation results. In addition, the proposed model is applicable to different electric network topologies and has the necessary flexibility of dealing with various problems during restoration.