Measurement Redundancy constrained Optimal PMU Locations

Modern power networks are operating under heavy stress due to the intrusion of unprecedented loads and unpredictable energy resources. Networks are operated at their peak capacity to meet the demand. These circumstances forced the operators to opt for Wide Area Measurements and Control (WAMC) schemes for real-time monitoring, control, and protection. Synchrophaosr technology has evolved as a promising technology for the implementation of WAMC. Phasor Measurement Units (PMUs) can provide the synchrophasor data along with frequency and Rate of Change of Frequency (ROCOF). Whereas the deployment of these devices was limited due to higher price tags. This constraint has been dealt with in this study by identifying the optimal locations for PMU placement considering the measurement redundancy.In the present study, the optimal PMU placement problem is formulated using binary decision variables (1,0) representing the existence or non-existence of PMU at that bus. Initially, an additive algorithm to solve linear problems with binary decision variables, Balas additive algorithm (BAA) is tested to solve the optimal PMU placement problem. After understanding the challenges a nature-inspired algorithm, Binary Particle Swarm Optimization (BPSO) technique is used to solve the problem. While maintaining the complete system observability, the presence of Zero Injection Busses (ZIB) is also exploited to reduce the count of PMUs. Consequences of optimal placement problem (OPP) like, measurement reliability is also addressed considering redundancy in measurements. Finally, the existence of multiple solutions was solved by introducing Bus Observability Index (BOI) and the System Observability Redundancy Index (SORI) rankings. Algorithms are tested on standard IEEE systems. Results have shown, less than 25% of the busses demanded PMU placement for full system observability, at the same time the number of installations increased with measurement redundancy.