LV State estimation in distribution power system, because of lack of real time measurements, must heavily rely on pseudo-measurements, primarily originating from standard load profiles. Actual load profiles have been recently suspected of deviating significantly from the standard load profiles, and research work is ongoing to quantify and characterize this deviation and to synthesize more realistic profiles. The analysis of the propagation of error and uncertainty of load profiles in state estimation must be investigated, as distribution system state estimation (DSSE) state estimation in distribution is being experimentally deployed, and the use of any available source of data is under consideration. The findings provide hints on the accuracy to be expected and on corrections to be applied to classical pseudo-measurements.

Distribution networks present their own features, significantly different from transmission systems features. For instance, loads are often unbalanced on the phases of the network. Moreover, the increasing amount of distributed generation, installed in an unplanned manner, is creating significant challenges. Such changing scenario imposes new operational requirements, such as distributed voltage control and demand side management. New performances are required for distribution system state estimators. In this paper, a study on the impact of different uncertainty sources on a state estimator designed for monitoring unbalanced distribution networks is presented. The impact of different measurement devices and levels of knowledge of the network behavior is analyzed and discussed using simulations performed on the 123-bus IEEE distribution network, which is commonly used as test network for this kind of stud

To deal with the increasing complexity of distribution networks that are experiencing important changes, due to the widespread installation of distributed generation and the expected penetration of new energy resources, modern control applications must rely on an accurate picture of the grid status, given by the distribution system state estimation (DSSE). The DSSE is required to integrate all the available information on loads and generators power exchanges (pseudomeasurements) with the real-time measurements available from the field. In most cases, the statistical behavior of the measured and pseudomeasured quantities cannot be approximated by a Gaussian distribution. For this reason, it is necessary to design estimators that are able to use measurements and forecast data on power flows that can show a non-Gaussian behavior. In this paper, a DSSE algorithm based on Bayes's rule, conceived to perfectly match the uncertainty description of the available input information, is presented. The method is able to correctly handle the measurement uncertainty of conventional and synchronized measurements and to include possible correlation existing between the pseudomeasurements. Its applicability to medium voltage distribution networks and its advantages, in terms of accuracy of both estimated quantities and uncertainty intervals, are demonstrated

Phasor Measurement Units have become more and more interesting for monitoring applications in distribution grids. For a large exploitation in medium and low voltage networks, however, a limited cost is required. Such specification, however, should not impact excessively the accuracy requirements, as it is expected that automatic control functionalities will run based on state estimation algorithms, which can be fed by PMU information. In this paper the design of a low cost PMU for distribution grids is proposed, and tested versus the IEEE c37.118.1-2011 standard for accuracy. The development of the low cost PMU is part of the Modular Intelligent Node (MIND) project, where distribution grid components and functionalities are implemented as modular interconnected nodes that run on general purpose hardware.(c) 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users.

The development of the smart grid requires new monitoring systems able to support automation functionalities to control Distributed Energy Resources (DERs). A real time Distribution System State Estimator (DSSE) integrated with bad data processor is presented in this work as a key element of the monitoring system. The developed DSSE is optimized for real time applications, particularly for computational efficiency, numerical stability and robustness against measurements with large error. The DSSE is localized within an automation platform, that performs monitoring and control at substation level, from which the requirements for monitoring are derived. DSSEs located in different automation platform may be coordinated through Multi Area algorithms, improving solution's time efficiency and robustness, but maintaining acceptable accuracy levels. The performance of real time DSSE, both for single and multi-area is analyzed and discussed by means of real time simulations performed in distribution Medium Voltage (MV) and Low Voltage (LV) networks.