Algoritmo para reconfiguração automática de redes de distribuição de energia baseado em critério de qualidade do fornecimento

Abstract

This work presents a new methodology for implementing reconfigurations of distribution networks in the face of contingency scenarios which lead to partial or total losses of network buses. The methodology consists of an algorithm capable of analyzing multiple contingency scenarios of a distribution network and, based on indicators of energy supply quality, proposing reconfiguration scenarios, while keeping automated the entire analysis and execution process automated. It also enables the classification of the best reconfiguration scenario among the possible ones, thus establishing the optimal scenario for the system reconfiguration. The selection and classification of the reconfiguration scenarios in terms of effectiveness is done through the FBR metric (Reconfiguration Benefit Factor) created in this work, which relates voltage, power, and line extension indicators added by the reconfiguration. Load flow simulations were performed using the OpenDSS software, which was controlled by the COM interface using the Python programming language for the algorithm structure. Based on the obtained results, the methodology proves to be effective, in which among the proposed reconfiguration scenarios, improvement in the network supply indicators was shown for each analyzed interruption scenario. Thus, the developed algorithm enables the analysis and study of network vulnerability, allowing for the implementation of reconfiguration in an automated manner. This procedure becomes advantageous when compared to the multiple contingency scenarios that may occur in a real distribution feeder, reducing the response and study time for network restoration. The proposed algorithm establishes itself as an aid tool for distribution network planning, in the scope of containment and mitigation of interruptions caused in the network, establishing optimal feeder reconfigurations, with criteria of energy quality and network extension, and can be implemented in an energy concessionaire, integrating the network planning and operation process