Improving power system stability after contingency occurrence on the Basis of Distributed Artificial Intelligence

Considering the importance of power system in national security of each country, stabilizing the network and protection against its collapse is the main concern of power system engineers. Employing Distributed Artificial Intelligence (DAI) theory and also Wide Area Monitoring, Protection And Control (WAMPAC) infrastructures lead to creation of a real time, wide, and flexible structure to control the power system and provide a robust system against contingency occurrence in the network. This study proposes a structure which provides power system stability after contingency occurrence on the basis of Multi Agent System (MAS). In this area, an algorithm has been proposed in the study where helps the control structure to prevent power system collapse after detection of wide area voltage violation. In order to test the proposed algorithm, DIgSILENT software has been utilized for simulation and the results are compared with conventional structure in order to validate the proposed structure.