Optimal Reconfiguration of Bipolar DC Networks Using Differential Evolution

Wesley Peres and Raphael Paulo Braga Poubel ()
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Wesley Peres: Department of Electrical Engineering, Federal University of São João del-Rei-UFSJ, São João del-Rei 36307-352, Brazil
Raphael Paulo Braga Poubel: Department of Electrical Engineering, Federal Center of Technological Education of Minas Gerais-CEFET-MG, Belo Horizonte 30510-000, Brazil

Energies, 2024, vol. 17, issue 17, 1-23

Abstract: The search for more efficient power grids has led to the concept of microgrids, based on the integration of new-generation technologies and energy storage systems. These devices inherently operate in DC, making DC microgrids a potential solution for improving power system operation. In particular, bipolar DC microgrids offer more flexibility due to their two voltage levels. However, more complex tools, such as optimal power flow (OPF) analysis, are required to analyze these systems. In line with these requirements, this paper proposes an OPF for bipolar DC microgrid reconfiguration aimed at minimizing power losses, considering dispersed generation (DG) and asymmetrical loads. This is a mixed-integer nonlinear optimization problem in which integer variables are associated with the switch statuses, and continuous variables are associated with the nodal voltages in each pole. The problem is formulated based on current injections and is solved by a hybridization of the differential evolution algorithm (to handle the integer variables) and the interior point method-based OPF (to minimize power losses). The results show a reduction in power losses of approximately 48.22% (33-bus microgrid without DG), 2.87% (33-bus microgrid with DG), 50.90% (69-bus microgrid without DG), and 50.50% (69-bus microgrid with DG) compared to the base case.

Keywords: bipolar DC microgrids; differential evolution; microgrids; optimal reconfiguration; power loss minimization; unbalanced operation (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2024
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