Reliability Enhancement of an 11kV Distribution Network Using Optimally Placed Hybrid Distributed Generation

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@article{1715520,
      author = {Digbani, O. S, Braide, S. L, Igbogidi, O. N},
      title = {Reliability Enhancement of an 11kV Distribution Network Using Optimally Placed Hybrid Distributed Generation},
      journal = {Iconic Research And Engineering Journals},
      year = {2026},
      volume = {9},
      number = {9},
      pages = {2941-2948},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1715520.pdf},
      abstract = {This paper presents a comprehensive techno‑analytical investigation into the impact of optimally placed hybrid distributed generation (DG) on the reliability performance of a medium‑voltage distribution network. A practical 11‑kV radial feeder in Edo State, Nigeria, supplying 2.01 MW of connected load, was used as the case study. In the base‑case condition, load‑flow and reliability analysis in ETAP yielded minimum bus voltages of 0.912 pu, total real power losses of 186.4 kW, and poor reliability indices of SAIFI = 13.58 interruptions/customer‑year, SAIDI = 49.35 hours/customer‑year, CAIDI = 3.63 hours/interruption and EENS = 314.74 MWh/year. Using a Genetic Algorithm implemented in MATLAB, two hybrid solar–wind DG units of optimal capacities 480 kW and 350 kW were allocated at Bus 9 and Bus 12, respectively. After DG integration, the minimum bus voltage improved to 0.981 pu, real power losses reduced to 74.2 kW (60.2% reduction), and reliability indices improved to SAIFI = 6.60 interruptions/customer‑year, SAIDI = 40.01 hours/customer‑year, CAIDI = 6.06 hours/interruption and EENS = 71.98 MWh/year, corresponding to a 77.1% reduction in energy not supplied. The results demonstrate that optimally placed hybrid renewable DG provides an effective technical solution for enhancing voltage stability, reducing losses and significantly improving service continuity in weak radial distribution networks.},
      keywords = {Distributed generation, Reliability indices, Genetic Algorithm, Hybrid renewable energy, Distribution system, ETAP, MATLAB},
      month = {March},
      doi = {https://doi.org/10.64388/IREV9I9-1715520}
  }