Journal of Modeling and Simulation in Electrical and Electronics Engineering

Journal of Modeling and Simulation in Electrical and Electronics Engineering

Harmony Search-Based Integrated Optimization of Distribution Networks Considering Feeder Reconfiguration, Capacitor Placement, and DG Allocation

Document Type : Research Article

Authors
1 Faculty of Electrical and Computer Engineering, Semnan University, Semnan, Iran.
2 Faculty of Electrical and Computer Engineering, Hakim Sabzevari University, Sabzevar, Iran.
Abstract
The optimization of distribution networks to minimize power losses and enhance voltage profiles remains a critical challenge in the design and operation of power systems. This study proposes an integrated optimization framework that simultaneously addresses network reconfiguration, optimal capacitor placement, and distributed generation (DG) allocation. The primary objective is to reduce active power losses and improve voltage quality by optimizing network topology and equipment deployment. To solve this problem, the Harmony Search Algorithm (HSA) is employed as an efficient metaheuristic method with strong adaptability to the nonlinear and combinatorial nature of distribution systems. The proposed model is implemented in MATLAB using the standard IEEE 33-bus test system. Simulation results demonstrate that the simultaneous application of network reconfiguration, capacitor placement, and DG integration achieves a significant reduction in power losses by up to 88.8% and voltage deviation by up to 47.9%, compared to the base case. These findings confirm the effectiveness of the proposed HSA-based framework in optimizing distribution network performance. The outcomes of this research can serve as a practical decision-support tool for distribution system operators, ultimately contributing to improved operational efficiency and economic benefits.
Keywords
Subjects

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Articles in Press, Accepted Manuscript
Available Online from 20 October 2026

  • Receive Date 24 May 2026
  • Revise Date 13 August 2026
  • Accept Date 17 August 2026