A GA based optimized PMU-location-decision algorithm considering WAMS reliability

Due to the unpredictable occurrences of serious blackout in power system, the importance of wide area measurement system has been highlighted. By using the data of phase measurement units (PMU) installed over the power grid, the indices of power system security and stability can be retrieved. As a result, based on the reflected dynamic information people have successfully implemented accurate power flow dispatch. However, one critical issue has to be pointed out that frequently monitoring devices are supposed to be reliable, which results in the overpass of secondary system failures in the researches of power system reliability. This may greatly impacts system operations and dispatching decision. To solve the issue, researchers have proposed a number of algorithms focusing on the improvements of the PMU availability. However, an individual PMU cannot fully describe the states of WAMS which can globally represent the power system states. And also their proposed work has less consideration that the secondary measuring system failure may be fed back into and impact the primary system. Consequently, a GA based optimized PMU-location-decision algorithm considering WAMS reliability is proposed in this paper. Firstly the algorithm computes the availability of PMU using Markov chains. Secondly in order to find the optimal deployment of PMU, the influence of PMU´s failure is analysed by the indices of WAMS reliability assessment. Finally by creating the `Energy-Information´ system scenario relational set with additional EDNS, the unestimated activities of primary system caused by PMU failure is analyzed. The experimental results show that along with the PMU failure rising the WAMS failure rate keeps rising, which generates uncertainty during the system operation. It also indicates through the redundant configuration of PMU, the reliability of system can be significantly enhanced.