Distributed multi-agent transmission system restoration using dynamic programming in an uncertain environment

In this paper, a decentralized multi-agent system (MAS) has been proposed to solve the power system restoration problem. In the proposed MAS, an agent with its own specific logic and interactions with other agents is devoted to any piece of equipment in the grid, including bus, black start, non-black start, photovoltaic and wind generating units. Power system restoration is devised as a single objective problem to minimize the energy not supplied (ENS), which is solved by bus agents using dynamic programming. The uncertainty of the wind and photovoltaic sources is considered in the corresponding agents, which is dealed by the Monte Carlo method. In addition, not only the genetic algorithm but also dynamic programming are employed in a top-down approach to solve the problem. The proposed algorithms are applied successfully to the IEEE 39-bus system. Comparing the results of both MAS and top-down approaches demonstrate that the proposed MAS outperforms the centralized method either optimized by genetic algorithm or dynamic programming in the sense of ENS.