Novos métodos de estimação de estado multi-área com potencial aplicação em redes elétricas inteligentes

Abstract

The smart grid will enable a revolution in the way we manage and relates to the distribution networks through intelligent applications. For many of these applications, it is understood that one of the primary activities to provide real time operation is to be aware of the electric state of the network by monitoring and using remote measurements. This thesis addresses the topic of state estimation proposing the use of methods that best fit the requirements of smart distribution networks. In a first moment it is understood that the monitoring will not be satisfactorily comprehensive, and then there will need to merge real measures with not real measures obtained through historical data and direct methods such as calculating the power flow. Another important requirement of these methods is to combine great complexity and large number of buses of the distribution network to a satisfactory response time that allows real-time monitoring. Thus this thesis uses an approach that enables multiprocessing of algorithms like Power Flow and State Estimation in order to get faster response times in multiprocessor environments, which now are quite common. In the case of State Estimator has been proposed a Multi-area estimator associated to an algorithm for massive division of the networks which allows to drastically reduce the complexity of the algorithm without compromising the accuracy of the estimator solution. Nevertheless, other concepts related to state estimation, but adapted to the context of smart grids are also addressed as the detection of errors in measurements, topology errors and to the ideal location of meters, which may have important influence on the accuracy of the obtained result. The ASW software - Analysis of Distribution Systems Web was developed to implement the proposed methodologies. The software is a totally working prototype, already tested on a real distribution networks and have demonstrated good results and potential for managing a distribution system in an smart way.