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A Framework for Constrained Static State Estimation in Unbalanced Distribution Networks

Marta Vanin, Tom Van Acker, Reinhilde D’hulst, Dirk Van Hertem

2021IEEE Transactions on Power Systems21 citationsDOI

Abstract

State estimation plays a key role in the transition from the passive to the active operation of distribution systems, as it allows to monitor the networks and provides the necessary information to perform control actions. However, designing state estimators for distribution systems is challenging, due to the characteristics of the networks, such as limited measurement availability. Furthermore, the features of the distribution system present significant local variations, e.g., voltage level and number and type of customers, which makes it hard to design a “one-size-fits-all” state estimator. This paper introduces a unifying framework that allows to easily implement and compare diverse unbalanced static state estimation models. This is achieved by formulating state estimation as a general constrained optimization problem. The advantages of this approach are described and supported by numerical illustration on a large set of real distribution feeders. The framework is also implemented in software and made available open-source.

Topics & Concepts

EstimatorComputer scienceState (computer science)Key (lock)Mathematical optimizationState estimatorSet (abstract data type)SoftwareControl engineeringEngineeringAlgorithmMathematicsComputer securityProgramming languageStatisticsOptimal Power Flow DistributionPower System Optimization and StabilitySmart Grid Energy Management
A Framework for Constrained Static State Estimation in Unbalanced Distribution Networks | Litcius