Abstract
In this paper two reconfiguration methodologies for three-phase electric power distribution systems based on multi-objective optimization algorithms are developed in order to simultaneously optimize two objective functions, (1) power losses and (2) three-phase unbalanced voltage minimization. The proposed optimization involves only radial topology configurations which is the most common configuration in electric distribution systems. The formulation of the problem considers the radiality as a constraint, increasing the computational complexity. The Prim and Kruskal algorithms are tested to fix infeasible configurations. In distribution systems, the three-phase unbalanced voltage and power losses limit the power supply to the loads and may even cause overheating in distribution lines, transformers and other equipment. An alternative to solve this problem is through a reconfiguration process, by opening and/or closing switches altering the distribution system configuration under operation. Hence, in this work the three-phase unbalanced voltage and power losses in radial distribution systems are addressed as a multi-objective optimization problem, firstly, using a method based on weighted sum; and, secondly, implementing NSGA-II algorithm. An example of distribution system is presented to prove the effectiveness of the proposed method.
Highlights
The power distribution system reconfiguration consists in altering the system topological structure by opening and closing some switching devices
In order to test the performance of both approaches, this paper proposes, first, to apply a Genetic Algorithm (GA) using the weighted sum method and reformulate the multi-objective problem into a single objective problem, applying a Multi-Objective Evolutionary Algorithms (MOEAs) to solve the same multi-objective problems for optimal distribution system reconfiguration
Considering standards used by utilities worldwide, as [32, 33], this paper implements the voltage unbalance factor (VUF) as the voltage unbalance index, which is the ratio between negative-sequence and positive-sequence voltage [34]
Summary
The power distribution system reconfiguration consists in altering the system topological structure by opening and closing some switching devices. MOEAs seem suitable to solve multi-objective optimization problems, because they deal simultaneously with a set of feasible solutions [9] This allows to find several members of the Pareto optimal set in a single run of the algorithm, instead of having to perform a serie of separate runs, as needed when using weighted sum. In order to test the performance of both approaches, this paper proposes, first, to apply a Genetic Algorithm (GA) using the weighted sum method and reformulate the multi-objective problem into a single objective problem, applying a MOEA to solve the same multi-objective problems for optimal distribution system reconfiguration. The system loads are altered to test the algorithms in an unbalanced system, and the system is extended to verify the efficiency of the proposed methods in larger unbalanced systems
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