Equivalent Circuit Programming for Estimating the State of a Power System

Abstract

An Equivalent Circuit Programming (ECP) approach that expresses the optimality conditions of an optimization problem in terms of an equivalent circuit model and uses circuit simulation techniques to solve for an optimal solution, is applied to the state estimation problem for power systems. The benefits of using an equivalent circuit formulation for incorporating both Phasor Measurement Units (PMU) and Remote Terminal Units (RTU), as well as for reducing the nonlinearities of the state estimation problem was previously demonstrated. In this paper we further exploit the circuit nature of the state estimation problem to formulate not only the model but also the optimality conditions as an ECP problem. The efficiency and accuracy of our approach are demonstrated by estimating the states of large-scale power grids (80k+ buses).

Enhanced Modelling Framework for Equivalent Circuit-Based Power System State Estimation

“…Poor computational speed of the NECF-SE estimator is mainly a consequence of the use of commerical nonlinear solver. However, it can be significantly improved by utilizing a circuit approach to solve the NECF-SE's optimization problem instead [22].…”

“…ECF has been leveraged recently to formulate a novel approach for SE in transmission systems, hence leading to the introduction of NECF-SE [20], [22] and LECF-SE [21] estimators. A brief overview of their similarities and differences will be presented below.…”

“…Due to the structure of the problem, it was solved by using commercial nonlinear solvers. Alternatively, the problem can be solved by formulating its optimality conditions in terms of equivalent circuit constraints [22]. In this way, the NECF-SE algorithm can be executed fully within the circuit domain.…”

“…The NECF-SE solved by nonlinear commercial solver proved to not be competitive with respect to computational speed. As an alternative, solving its optimization problem within the equivalent circuit framework is suggested to reduce the computational complexity, achieving significantly improved computational speed [22]. For consistency and given the fact that it is still slower than the LECF-SE, we omit the discussion of using this alternative solver.…”

A Probabilistic Approach to Power System State Estimation using a Linear Algorithm

“…Using this modeling approach and an optimization toolbox, a linear state estimation algorithm was introduced in [15]. Separately, it was demonstrated that it is possible to extend the ECF to natively solve optimization problems, including SE, within the same framework [16]- [18].…”