Resilient model for distribution networks regarding power flow based on graph theory

Abstract

 The resilience concept of distribution networks is an emerging issue, which is proposed as a solution against extreme weather conditions and can be a key factor in the strategy of development of sustainable energy. The infrastructure of the electrical network installed in the tropical region suffers a high degree of affectation due to the stochastic nature of weather. Therefore, this paper offers a routing resilient and deployment of the distribution network based on some meta-heuristic optimization algorithms, approach on the optimal location of the transformers and, minimum spanning tree (MST) based on the PRIM algorithm variant has been applied to find the optimum distribution network routing before, during and after an extreme weather condition, minimizing the distance associated to each bay as an objective function. It should be noted that the model was tested in a real geo-referenced scenario with static loads during the event, using algebraic system MATLAB. To solve the electrical feasibility, the power flow was simulated with the Cymdist software, taking into account the distances of the loads.