Revisiting the Optimal PMU Placement Problem in Multimachine Power Networks

Abstract

To provide real-time visibility of physics-based states, phasor measurement units (PMUs) are deployed throughout power networks. PMU data enable real-time grid monitoring and control - and are essential in transitioning to smarter grids. Various considerations are taken into account when determining the geographic, optimal PMU placements (OPPs). This article focuses on the control-theoretic, observability aspect of OPP. A myriad of studies have investigated observability-based formulations to determine the OPP within a transmission network. However, they have mostly adopted a simplified representation of system dynamics, ignored basic algebraic equations that model power flows, disregarded renewables such as solar and wind, and did not model their uncertainty. Consequently, this article revisits the observability-based OPP problem by addressing the literature's limitations. A nonlinear differential algebraic (NDAE) representation of the power system is considered. The system is discretized using various discretization approaches while explicitly accounting for uncertainty. A moving horizon estimation (MHE) approach is explored to reconstruct the joint differential and algebraic initial states of the system, as a gateway to the OPP problem, which is then formulated as a computationally tractable integer program (IP). Comprehensive numerical simulations on standard power networks are conducted to validate different aspects of this approach and test its robustness to various dynamical conditions.