Topology Optimization of Distribution Network Using an Efficient Linearized Model Considering Load Type

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Abstract
Distribution network reconfiguration stands out as a potent approach for reducing power losses in radial distribution feeders, where losses notably are more those observed in transmission systems. The distribution power losses incurred not only lead to costly operations but also contribute to a compromised voltage profile in electric energy grids. Habitual reconfiguration involves adjusting the form of the distribution grid to minimize electric energy losses, with a focus on the electricity demanded by end-consumers. The existing models predominantly address distribution network reconfiguration without accounting for the different types of load demand linked to points of consumption, each exerting distinct power loss effects in contrast to single-type demands. Despite the imperative load type diversity role, most models neglect this aspect. The limited studies incorporating load type into reconfiguration strategies tend to employ non-linear formulations, introducing complexities. While models with non-linear characteristics may be tackled via metaheuristic techniques, they fall short of guaranteeing optimal solutions. Alternatively, solving such models using solvers for non-linear equations in conventional tools of optimization demands computations that require significant time. To address these challenges, the present article proposes an impressive model for reconfiguring distribution networks that consider different load types. Notably, this model is designed for seamless implementation with linear procedures. Our study’s results demonstrate the exactitude of the introduced model in yielding accurate results for targeted reconfiguration challenges, coupled with the advantage of swift execution suitable for real-time reconfigurations.

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