Deregulation and privatization actions are creating new problems of control, management and reliability, because of new players and new technologies spreading in distribution systems. Such new scenarios require more comprehensive and accurate knowledge of the system to make control actions efficient and reliable. In particular, attention must be paid to phase angles estimation to avoid critical situations. In this context, the use of phasor measurement units (PMUs) looks promising. This paper presents an efficient branch-current-based distribution systems state estimation. The estimator allows synchronized phasor measurements provided by PMUs to be included. In addition, the branch current state model is extended so that the knowledge of the voltage profile is significantly improved. The estimator is expressed both in polar and rectangular coordinates and a comparison between the obtainable accuracy and computational efficiency is presented. Furthermore, the possibility to treat radial and weakly meshed topology, also in presence of dispersed generation, is analyzed. The results obtained on different distribution networks are presented and discussed.

Future active distribution grids are characterized by rapid and significant changes of operation and behavior due to, for example, intermittent power injections from renewable sources and the load-generation characteristic of the so-called prosumers. The design of a robust measurement infrastructure is critical for safe and effective grid control and operation. We had earlier proposed a placement procedure that allows finding an optimal robust measurement location incorporating phasor measurement units and smart metering devices for distribution system state estimation. In this paper, the lack of detailed information on distributed generation is also considered in the optimal meter placement procedure, so that the distributed measurement system can provide accurate estimates even with limited knowledge of the profile of the injected power. Possible non-Gaussian distribution of the distributed power generation has been taken into account. With this aim, the Gaussian mixture model has been incorporated into the placement optimization by means of the so-called Gaussian component combination method. The occurrence of either loss of data or degradation of metrological performance of the measurement devices is also considered. Tests performed on a UKGDS 16-bus distribution network are presented and discussed.

The distribution grid is the infrastructure that transports electrical energy generated by large plants that are long distances away to the final user. A typical distribution grid consists of High-to-Medium Voltage (HV/MV) transformation centers; the MV grid; Medium-to-Low Voltage (MV/LV) transformation centers; and the LV grid, both three-phase and single-phase. Residential and commercial customers are mainly connected to the LV, while large industrial facilities are connected to the MV.

Distribution system state estimation (DSSE) is one of the key elements of the monitoring activity of an active distribution network, and is the basis for every control and management application. The DSSE relies on real measurements collected by the distributed measurement system and on other available information, mainly obtained from historical data that help in obtaining observability. This prior information is necessary to derive the so called pseudomeasurements. Accurate input data are fundamental for an accurate estimation, as well as knowledge on possible correlation in the measured and pseudomeasured data. A degree of correlation can exist in the measured data, due to measurement devices, and among power consumptions or generations of some particular nodes. This paper presents an exhaustive analysis on the influence of correlations on the quality of the estimation. The importance of including correlation in the weighted least square estimation approach is discussed using both traditional and synchronized measurements. Results obtained on a 95-bus distribution network are presented and discussed.

Energy management systems for the operation of distributed energy resources, distribution storage devices, and responsive loads will be embedded in distribution management systems (DMSs) as advanced functions that rely on accurate input data and fast communication signals. For a proper DMS design, the impact of the state estimation uncertainties and of the communication system delays should be evaluated. The paper presents an integrated software package for the cyber-physical simulation of DMS taking into account the accuracy of state estimation and measurements. The effectiveness of a wireless Wi-Max communication system has been tested on the rural Italian representative network produced by the research project ATLANTIDE. Results proved the need of cosimulation packages in modern distribution systems.

This paper presents a new approach to the distribution system state estimation in wide-area networks. The main goal of this paper is to present a two-step procedure designed to accurately estimate the status of a large-scale distribution network, relying on a distributed measurement system in a multiarea framework. First of all, the network is divided into subareas, according to geographical and/or topological constraints and depending on the available measurement system. Then, in the first step of the estimation process, for each area, a dedicated estimator is used, exploiting all the measurement devices available on the field. In the second step, data provided by local estimators are further processed to refine the knowledge on the operating conditions of the network. To improve the accuracy of the estimation results, correlation arising in the first step estimations has to be suitably evaluated and considered during the second step. Performed analysis shows that existing correlations can be included in the estimation process with very low data exchange among areas, thus involving minimum communication costs. Both first and second steps can be performed in a decentralized way and with parallel processing, thus leading to reduced overall execution times. Test results, obtained on the 123-bus IEEE test network and proving the goodness of the proposed method, are presented and discussed.