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

Considering the importance of power networks in national security, power system stability under critical conditions such as occurrence of contingencies is the most important concern of power system engineers and government. In this area, employing Distributed Artificial Intelligence (DAI) theory and also Wide Area Monitoring, Protection And Control (WAMPAC) infrastructures may help to create a flexible organization where provides a robust system against contingency occurrence. This study proposes an adaptive structure on the basis of Multi Agent System (MAS). In this context, an algorithm has been proposed which helps the control system to save power system from collapse after detection of wide area voltage violation. Also, in order to verify the proposed algorithm, DIgSILENT software has been employed to simulate and the results are compared with conventional structures such as central control system and also unsupervised control structure.