Evaluation of Distribution System Reliability with Intelligent Placement of Distributed Generation (Case Study: Eastern Ethiopia Wuchale Distribution Feeder)

Abstract:

In the competitive electric utility market, prioritizing reliability assessment is crucial to meeting customer satisfaction. Distributed generation (DG) is considered the most effective alternative to enhance performance and increase the reliability of the distribution system. In the Jigjiga distribution system, there were problems with overloading, short circuits due to old or damaged electrical devices, improperly allocated distribution transformers, less maintenance, limited protective devices, etc. In this distribution system, there are four 132/33 kV and four 132/15 kV distribution feeders. The two-year period data (2021 and 2022 G.C.) frequency of interruption and duration of interruption data have been collected from the EEU recorded data center for all Jigjiga 33 kV and 15 kV distribution feeders. The reliability of an electric power distribution system at Wuchale's 132/33 kV feeder is evaluated due to its frequent interruptions and long-distance coverage from the supply point. The Wuchale 132/33 kV feeder, serving 2563 customers, includes 54 distribution transformers. This study aims to evaluate the reliability and value of the Wuchale feeder by incorporating distributed generation (DG) using the PSO algorithm for optimal DG allocation. Simulations have been conducted using DigSILENT PowerFactory. The initial reliability indices for the Wuchale feeder were SAIFI = 200.38, SAIDI = 6441.13, CAIDI = 32.143, ASAI = 0.264, and ASUI = 0.735, exceeding the Ethiopian standard of SAIFI = 20 and SAIDI = 25. After optimal distribution generation allocation, the indices improved significantly to SAIFI = 17, SAIDI = 28, CAIDI = 1.647, ASAI = 0.996, and ASUI = 0.003. This integration of DG reduced the SAIFI and CAIDI indices by 82% and 90%, respectively. The proposed solution also resulted in an annual savings of 6,071,335.2 ETB from unsold energy, with a payback period of 6.45 years. The PSO algorithm identified buses 3, 14, and 45 for distributed generation allocation.

• Periodical: Advanced Engineering Forum (Volume 55)
• Pages: 91-114
• DOI: https://doi.org/10.4028/p-JbHW59
• Online since: May 2025
• Authors: Yechale Amogne Alemu*, Tefera Terefe Yetayew, Yechale Atinafu Temesgen, Eyob Abayneh Tegegn
• Keywords: DigSILENT PowerFactory, Distributed Generation (DG), Ethiopian Electric Utility (EEU), Particle Swarm Optimization (PSO), Photovoltaic (PV) System, Reliability Assessment

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