An efficient method to include equality constraints in branch current distribution system state estimation

Distribution system state estimation is a fundamental tool for the management and control functions envisaged for future distribution grids. The design of accurate and efficient algorithms is essential to provide estimates compliant with the needed accuracy requirements and to allow the real-time operation of the different applications. To achieve such requirements, peculiarities of the distribution systems have to be duly taken into account. Branch current-based estimators are an efficient solution for performing state estimation in radial or weakly meshed networks. In this paper, a simple technique, which exploits the particular formulation of the branch current estimators, is proposed to deal with zero injection and mesh constraints. Tests performed on an unbalanced IEEE 123-bus network show the capability of the proposed method to further improve efficiency performance of branch current estimators

Security in power system state estimation

With the power system evolving from passive to a more active system there is an incorporation of information and communication infrastructures in the system. The measurement data are more prone to tampering from attackers for mala fide intentions. Therefore, security and reliability of distribution have become major concerns. State estimation (SE), being the core function of the energy/distribution management system (EMS/DMS), has become necessary in order to operate the system efficiently and in a controlled manner. Although SE is a well-known task in transmission systems, it is usually not a common task in unbalanced distribution systems due to the difference in design and operation philosophy. This thesis addresses these issues and investigates the distribution system state estimation with unbalanced full three-phase modelling. The formulation, based on weighted least squares estimation, is extended to include the open/closed switches as equality constraints. This research then explores the vulnerabilities of the state estimation problem against attacks associated with leverage measurements. Detecting gross error particularly for leverage measurements have been found to be difficult due to low residuals. The thesis presents and discusses the suitability of externally studentized residuals compared to traditional residual techniques. Additionally, the masking/swamping phenomenon associated with multiple leverages makes the identification of gross error even more difficult. This thesis proposes a robust method of identifying the high leverages and then detecting gross error when the leverage measurements are compromised. All algorithms are validated in different IEEE test systems.Open Acces

Combined Unbalanced Distribution System State and Line Impedance Matrix Estimation

To address the challenges that the decarbonization of the energy sector is bringing about, advanced distribution network management and operation strategies are being developed. Many of these strategies require accurate network models to work effectively. However, distribution network data are known to contain errors, and attention has been given to techniques that allow to derive improved network information. This paper presents a novel method to derive line impedance values from smart meter measurement time series, with realistic assumptions in terms of meter accuracy, resolution and penetration. The method is based on unbalanced state estimation and is cast as a non-convex quadratically constrained optimization problem. Both line lengths and impedance matrix models can be estimated based on an exact nonlinear formulation of the steady-state three-phase network physics. The method is evaluated on the IEEE European Low Voltage feeder (906 buses) and shows promising results