Realistic Approach for Phasor Measurement Unit Placement: Consideration of Practical Hidden Costs

Abstract

This paper presents a realistic cost-effective model for optimal placement of phasor measurement units (PMUs) for complete observability of a power system considering practical cost implications. The proposed model considers hidden or otherwise unaccounted practical costs involved in PMU installation. Consideration of these hidden but significant and integral part of total PMU installation costs was inspired from practical experience on a real-life project. The proposed model focuses on the minimization of total realistic costs instead of a widely used theoretical concept of a minimal number of PMUs. The proposed model has been applied to IEEE 14-bus, IEEE 24-bus, IEEE 30-bus, New England 39-bus, and large power system of 300 buses and real life Danish grid. A comparison of the presented results with those reported by traditional methods has also been shown to justify the effectiveness of the proposed model with regard to its realistic and practical nature.Index Terms-KCL, KVL, optimal placement of PMUs, phasor measurement units (PMUs), power system observability.

PMU Placement in Electric Transmission Networks for Reliable State Estimation Against False Data Injection Attacks

“…[17][18][19]) are available to address the issue of optimal PMU placement with different objectives and deployment constraints. The optimal PMU placement can be obtained through minimizing the cost of overall WAMS (PMUs, phasor data concentrators and communication infrastructures (CIs)) [17].…”

“…An optimization formulation was proposed in [18] to improve the measurement redundancy with minimum number of PMUs while maintaining full system observability. The work in [19] focused on the minimization of total realistic cost with considering hidden but significant and integral part of PMU installation cost. The work in [27] developed a mixed integer programming model for optimal PMU deployment and optimal selection of existing PMUs to mitigate sparse unobservable attacks.…”

A PMU Placement Scheme Considering Realistic Costs and Modern Trends in Relaying

“…Mathematical techniques applied to solve the OPP problem include genetic algorithms [4], linear programming [5], semi-definite programming [6], particle swarm optimization [7], Tabu search [8], etc.…”

Artificial Intelligence Versus Conventional Mathematical Techniques: A Review for Optimal Placement of Phasor Measurement Units

“…Then, the effect of PMU loss or a branch outage was taken into consideration, and a placement scheme was obtained which maintains complete sys-tem observability during the contingency conditions. In [23,24] PSO optimization is also used for obsevability with the objective of minimum cost of PMU.…”