Prototype and monitoring system of phasor measurement unit based on the internet of things

Abstract

This research resulting the method to reduce phasor measurement unit (PMU) amount and optimization of PMU replacement using a combination of Integer linear k-means. The first step of modeling is using a lot of PMUs that are optimized at Bendul Merisi network using integer linear k-means clustering for achieving an optimum solution of amount and replacement of PMU to be installed. The second step is estimating the uninstalled bus's power and voltage. PMU is using modified adaptive neuro-fuzzy inference system (ANFIS) of hybrid particle swarm optimization (PSO)-genetic algorithm (GA). The third step is to test and simulate the hardware design of the research for offline and online data. Research also tested network transmission of Java–Bali 500 kV. Designed simulation can calculate the active and reactive power of each bus in clusters so the total active and reactive power of each cluster can be known. Device tests to transmit data using internet of things (IoT) from a laboratory scale during 7 days have an average of 2.8 seconds while the field test required an average of 10.416 seconds during 24 hours.