An efficient heuristic algorithm for reconfiguration based on branch power flows direction

This paper presents a meshed algorithm for optimal reconfiguration of distribution systems. In the reconfiguration problem, the final objective is to reach a radial network that optimizes some function like the network losses. Many algorithms start from a radial network where a switch closure is complemented by opening of another switch to ensure a radial network. These radial algorithms have an inherent inconvenient, that is, the final solution depends on the initial radial network selected. Other group of algorithms initially represent the distribution network as a meshed network and then open switches until a radial system is obtained. In this paper, to avoid the above aforementioned inconvenient of radial algorithms, a meshed algorithm is used. Furthermore, taking into account that breakpoint nodes are defined as the nodes where the branch power flows converge, the contribution of this paper is to provide a method for solving the problem when multiple loops are considered using an approach based on the breakpoint nodes, since it is complicated to associate each breakpoint node with its corresponding loop. On the other hand, one of the drawbacks of the reconfiguration problem is the need to solve a great number of power flow computations for calculating the losses in each stage of the algorithm. The algorithm proposed has the property that reduces the number of power flows. By this way, the execution time of the algorithm is improved. Besides, it is not necessary to check the network connectivity at each step of the procedure. To prove the effectiveness of the proposed algorithm several test systems have been used, achieving good results.

► It is not necessary to check the network connectivity.
► The heuristic is based on power flow directions.
► Breakpoint nodes for solving the minimum loss reconfiguration problem.
► We have paired off active and reactive breakpoint nodes in a meshed network.
► The obtained results are equal or better than those published in the literature.