Network Reconfiguration for Loss Reduction Using Tabu Search and a Voltage Drop

Dionicio Zocimo Ñaupari Huatuco (), Luiz Otávio Pinheiro Filho, Franklin Jesus Simeon Pucuhuayla and Yuri Percy Molina Rodriguez ()
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Dionicio Zocimo Ñaupari Huatuco: Faculty of Electrical Engineering, National University of Engineering, Lima 15333, Peru
Luiz Otávio Pinheiro Filho: Center of Alternative and Renewable Energy, Federal University of Paraíba, João Pessoa 58051-900, PB, Brazil
Franklin Jesus Simeon Pucuhuayla: Faculty of Electrical Engineering, National University of Engineering, Lima 15333, Peru
Yuri Percy Molina Rodriguez: Center of Alternative and Renewable Energy, Federal University of Paraíba, João Pessoa 58051-900, PB, Brazil

Energies, 2024, vol. 17, issue 11, 1-18

Abstract: This paper introduces a new algorithm designed to address the challenge of distribution network reconfiguration, employing the tabu search metaheuristic in conjunction with the voltage drop concept. Distinguishing itself from existing methods, our proposed approach not only utilizes voltage drop for obtaining the initial solution but also introduces a novel technique for generating a candidate solution neighborhood. This method leverages both randomness and voltage drop, ensuring a smooth and steady descent during algorithm execution. The primary goal of our algorithm is to minimize active power losses within distribution networks. To validate its effectiveness, the proposed method underwent testing on three commonly referenced distribution systems: the 33-Bus, 69-Bus, and 94-Bus systems, widely acknowledged in the literature. A pivotal aspect of our work involves the synergy of the tabu search algorithm with a combination of both random and deterministic methods for generating neighbors. This strategic amalgamation plays a crucial role, enabling rapid execution while consistently yielding high-quality solutions. Additionally, the adoption of the electric distance method for generating the initial solution adds significant value, offering a commendable solution with minimal computational effort. Comparative assessments against other algorithms documented in the literature underscore the superior efficiency of our proposed algorithm.

Keywords: network reconfiguration; distribution system; optimization; tabu search; minimization; distribution system loss; OpenDSS; Python (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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