Hierarchical Clustering based optimal PMU placement for power system fault observability

Abstract

Optimal number and location of phasor measurement units (PMUs) in the power system networks faces challenges for achieving the full network observability during fault conditions. Achieving fault observability approach requires more constraints than normal system observability and consequently suffers from complex analysis and heavy computational burden for the large-scale networks. A new algorithm for determining the optimal PMU placement considering the network fault observability is introduced. The proposed algorithm is achieved through four stages. The first stage is achieved through the network fault simulation to obtain the post fault change in voltage (ΔV) at each bus. Then, the post fault change in voltage (ΔV) is used to build the network connectivity matrix (CM) and forming a new developed Faulted Connectivity Matrix (FCM) that describes the power system topology during the fault conditions. The correlation between the buses is obtained, in the second stage, by applying Pearson correlation coefficient. Hierarchical Clustering technique is given, in the third stage, to cluster the network into coherent zones to find the most correlated buses. Finally, the optimal location of the PMUs is identified within each zone based on simple proposed placement rules. The proposed algorithm is tested under a variety of fault events applied on different standard test systems. The results show the simplicity and the effectiveness of the proposed algorithm.

Optimal location of PMUs for full observability of power system using coronavirus herd immunity optimizer

“…In this study, the following rules are considered in fault observability analysis using PMUs These rules are derived from Refs. [ 33 , 40 , 41 ]. For any TL to become fault-observable, information on both end buses' voltage phasors and the phasor of fault current fed from its two terminals should be available.…”

“…Many researchers have discussed the OPP scheme for locating faults in power systems [ [28] , [29] , [30] , [31] , [32] , [33] , [34] ]. Ref.…”

“…Researchers in Refs. [ [30] , [31] , [32] , [33] , [34] ] have discussed this problem to obtain the optimal placement and minimum number of PMUs for full system observability in both normal and faulty conditions. In Ref.…”

“…A hierarchical clustering technique was applied in Ref. [ 33 ] to split the power system into coherent areas to determine the most relevant buses to attain complete power system observability during faults. Then the optimal PMUs’ locations were determined for every area depending on simple rules.…”

Smart Grid to Energy Internet: A Systematic Review of Transitioning Electricity Systems

“…Energy consumers take appropriate decisions based on the information shown in the in-home displays [29]. For instance, company called smarter homes [30] deploy home energy management technologies using internet-of-things and consumer electronic devices like iPad and Amazon Alexa to control the solar rooftop PV, storage devices, and home appliances. Home energy management systems aid coupling of energy storage to the household system.…”