Abstract
In the modern power system networks, grid observability has greatly increased due to the deployment of various metering technologies. Such technologies enhanced the real-time monitoring of the grid. The collection of observations are processed by the state estimator in which many applications have relied on. Traditionally, state estimation on power grids has been done considering a centralized architecture. With grid deregulation, and awareness of information privacy and security, much attention has been given to multi-area state estimation. Considering such, state-of-the-art solutions consider a weighted norm of residual measurement model, which might hinder masked gross errors contained in the null-space of the Jacobian matrix. Towards the solution of this, a distributed innovation-based model is presented. Measurement innovation is used towards error composition. The measurement error is an independent random variable, where the residual is not. Thus, the masked component is recovered through measurement innovation. Model solution is obtained through an Alternating Direction Method of Multipliers (ADMM), which requires minimal information communication. The presented framework is validated using the IEEE 14 and IEEE 118 bus systems. Easy-to-implement model, build-on the classical weighted norm of the residual solution, and without hard-to-design parameters highlight potential aspects towards real-life implementation.
Highlights
Power System State Estimation (PSSE) was originally introduced by Schweppe in the early 1970s [1], and the operation of the grid has relied on such model ever since
This paper presents a distributed non-linear multi-area state estimator which is based on the Gauss solution
R N, (m > N ) is a non-linear differentiable function that relates the states to the measurements, e is the measurement error vector assumed with zero mean, standard deviation σ and having Gaussian probability distribution, and N = 2n − 1 is the number of unknown state variables
Summary
Power System State Estimation (PSSE) was originally introduced by Schweppe in the early 1970s [1], and the operation of the grid has relied on such model ever since. One main characteristic of Distributed State Estimation (DSE) is enabling regional control centers to perform their own SE process with enhanced robustness. Each local control center performs their own SE, and upon convergence, estimated states are communicated with a central control for coordination. The main shortcoming of this method is that there is still a need for a central controller to consent the global estimation of the states by matching with the boundary bus measurements. This paper presents a distributed non-linear multi-area state estimator which is based on the Gauss solution. A distributed measurement model for non-linear multi-area state estimation which utilizes ADMM; Applying the Innovation Concept, which takes into account the masked error component in the Jacobian range space
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