Novel Clustering-based Hidden Markov Model (CHMM) optimization approach for optimal PMU placement

Abstract

A Phasor Measurement Unit (PMU) is an important device for monitoring the wide-area power distribution network. Placement of the PMUs across the network enables reliable monitoring of the network to identify the faults in the bus system. Due to the increase in the installation cost of the PMUs, optimal placement of the PMU is a significant task. But the existing techniques do not provide the optimal solution for the PMU placement. To overcome this issue, this paper proposes a novel Clustering-based Hidden Markov Model (CHMM) optimization approach to achieve optimal placement of PMUs in the power distribution network. Optimal PMU placement is achieved by applying cluster formation in the bus system to extract the data with neighboring buses. Best optimal position for placing the PMU is estimated by using Fuzzy logic-based rale formation to update the binary table of the bus system. The HMM approach is used for updating weight in the cluster formation. Our system is implemented in various bus systems like IEEE 28-bus system, 69-bus system and also in Karnataka 155-bus system. The proposed approach is implemented in the IEEE bus system and Karnataka Power Transmission Corporation Limited (KPTCL) bus system and compared with the existing approaches, based on the total number of PMU placement. The proposed approach achieves better performance in the optimal placement of PMU than the existing optimization algorithms.