Modelagem e implementação de lógica de determinação de operações de reconfiguração de redes de distribuição no opendss integrado ao Python

Abstract

Distribution network reconfiguration is an important strategy to reduce the impact of power supply interruptions, especially in radial systems where the opening of a single section may disconnect a large portion of the network. This work presents the development and implementation of an algorithm for the automatic determination of distribution network reconfiguration options, based on the identification and execution of an optimal switching sequence, using the OpenDSS electrical simulator integrated with the Python programming language. The proposed methodology comprises: (i) modeling the IEEE 123-bus test feeder; (ii) extracting the electrical topology and building an SQLite database containing network connections, switches, loads, and spatial coordinates; (iii) developing a deterministic algorithm capable of identifying the section to be isolated, selecting the initial normally closed switch (NC) for isolation, determining the most suitable normally open switch (NO) for load restoration based on maximum load recovery, and applying the final containment switch (NC); and (iv) performing electrical validation of the switching operations using OpenDSS load flow simulations. For operational use, an interactive platform was developed using Streamlit, allowing the user to select the desired network section and automatically visualize the reconfiguration sequence, as well as the interrupted and restored loads. The results demonstrate that the implemented algorithm consistently isolates network sections, minimizes interrupted load, and restores service in a structured and traceable manner, highlighting the potential of Python–OpenDSS integration as a decision-support tool for distribution networks.