A Multiarea State Estimation for Distribution Networks Under Mixed Measurement Environment

Abstract

A grand challenge for the state estimation (SE) method in large-scale distribution networks lies in how to deal with the increasing computational tasks. This article addresses the issue and proposes a novel multiarea architecture for the unbalanced distribution network SE method. The first step of the method is to introduce an innovative multiarea state estimation (MASE) model using microphasor measurement units ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">μ</i> PMU) mixed with conventional supervisory control and data acquisition (SCADA) systems, with both the coordinate tensions and synchronization issues considered. The proposed model contains a SCADA measurement delay estimator and a MASE algorithm. Then, the hybrid state estimation (HSE) model is solved in a distributed way. In each subarea, the HSE problem is solved locally with minimal data exchanges among neighbor subareas. Case studies show the accuracy and efficiency enhancements obtainable of the proposed MASE method with respect to existing ones.