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.
Multiarea Distribution System State Estimation
MUSCAS, CARLO;PEGORARO, PAOLO ATTILIO;SULIS, SARA;
2015-01-01
Abstract
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.File | Dimensione | Formato | |
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