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article · Journal of Electrical Systems and Information Technology

A comparative study of distribution static compensator and distribution generation for techno-economic performances by optimizing location and sizing through intelligent systems (case study: Bahir Dar distribution network)

2026Open accessWoldia University

Abstract

Abstract Radial distribution networks are often characterized by high active and reactive power losses, poor voltage profiles, and weak voltage stability. Addressing these challenges requires the deployment of effective reinforcement strategies. This study presents a comparative techno-economic analysis of Distributed Generators (DGs) and Distribution Static Compensators (D-STATCOMs) in the 68-bus R5-G3 feeder of the Bahir Dar distribution system. A multi-objective function (MOF) was formulated to minimize real and reactive losses, improve voltage profile, and enhance the voltage stability index, subject to bus voltage, power balance, and device capacity constraints. The optimization was solved using Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and a hybrid GA-PSO approach, with load flow analysis based on the BIBC–BCBV direct method. Simulation results show that DGs reduce active power loss by up to 65% and raise the minimum bus voltage from 0.8771 p.u. (base case) to 0.9632 p.u., while D-STATCOMs achieve up to 61% loss reduction and comparable voltage support. Economic evaluation reveals that DGs involve higher capital cost and longer payback periods (4–6.4 years), whereas D-STATCOMs are more cost-effective, with a minimum payback of 2.6 years under GA-PSO optimization. The study concludes that while DGs deliver superior technical improvements, D-STATCOMs offer stronger economic feasibility. These insights are directly relevant to Ethiopian Electric Utility for practical planning and provide a comparative benchmark for researchers on coordinated deployment of DG and D-STATCOM technologies.

Research topics

  • Optimal Power Flow Distribution
  • Power System Optimization and Stability
  • Electricity Theft Detection Techniques

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DOI: 10.1186/s43067-026-00319-z

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