Scenario-based optimization of standalone microgrids using PSO: comparative assessment of hybrid configurations for off-grid electrification in Unguja Island

Fathia Jombi Kheir; Soichiro Ueda; Takuma Ishibashi; Mitsunaga Kinjo; Issoufou Tahirou Halidou; Masahiro Furukakoi; Tomonobu Senjyu; Fathia Jombi Kheir; Soichiro Ueda; Takuma Ishibashi; Mitsunaga Kinjo; Issoufou Tahirou Halidou; Masahiro Furukakoi; Tomonobu Senjyu

doi:10.3934/energy.2025035

AIMS Energy

2025, Volume 13, Issue 4: 938-961. doi: 10.3934/energy.2025035

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Research article

Scenario-based optimization of standalone microgrids using PSO: comparative assessment of hybrid configurations for off-grid electrification in Unguja Island

1.
Faculty of Engineering, University of the Ryukyus, Okinawa 903-0213 Japan
2.
Sanyo-Onoda City University, Yamaguchi, 756-0884, Japan

Received: 05 June 2025 Revised: 27 July 2025 Accepted: 08 August 2025 Published: 19 August 2025

Access to a sustainable and reliable power supply has been a major struggle for most remote and rural communities, particularly on Islands. This is largely due to the uncertainties and vulnerabilities imposed by grid extension and electricity importation. This study employed a Particle Swarm Optimization (PSO) approach to assess the performance of three off-grid microgrid configurations: PV/BESS, PV/Wind/BESS, and PV/BESS/DG for electrifying a village in the northern region of Unguja Island. The effective sizing was conducted using real-time and site-specific meteorological and demand data. The primary goal was to minimize the Levelized Cost of Energy (LCOE) while satisfying the reliability constraint defined as the Loss of Power Supply Probability (LPSP), below 4%. The results demonstrated that the PV/Wind/BESS configuration exhibited the lowest LCOE at $ \$ $0.014/kWh; 13.6% and 46.2% lower than the PV/BESS and PV/BESS/DG configurations, respectively. Although the PV/BESS/DG scenario demonstrated greater reliability compared to other cases, it incurred the highest LCOE over the project lifetime, which was attributed to volatile fuel prices and elevated operational costs. Furthermore, the sensitivity analysis highlighted the substantial influence of life-cycle costs, including component replacement and operational maintenance costs, on the long-term economic viability of the proposed microgrid configurations. These insights offer valuable strategic guidance for energy policymakers aiming to enhance energy security and autonomy in rural and underserved communities.
- Off-grid Microgrids,
- Levelized Cost of Energy,
- Loss of Power probability,
- PSO,
- PV system,
- Wind energy System,
- DG system,
- Zanzibar,
- CO$ _2 $ emissions
Citation: Fathia Jombi Kheir, Soichiro Ueda, Takuma Ishibashi, Mitsunaga Kinjo, Issoufou Tahirou Halidou, Masahiro Furukakoi, Tomonobu Senjyu. Scenario-based optimization of standalone microgrids using PSO: comparative assessment of hybrid configurations for off-grid electrification in Unguja Island[J]. AIMS Energy, 2025, 13(4): 938-961. doi: 10.3934/energy.2025035

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Abstract

Access to a sustainable and reliable power supply has been a major struggle for most remote and rural communities, particularly on Islands. This is largely due to the uncertainties and vulnerabilities imposed by grid extension and electricity importation. This study employed a Particle Swarm Optimization (PSO) approach to assess the performance of three off-grid microgrid configurations: PV/BESS, PV/Wind/BESS, and PV/BESS/DG for electrifying a village in the northern region of Unguja Island. The effective sizing was conducted using real-time and site-specific meteorological and demand data. The primary goal was to minimize the Levelized Cost of Energy (LCOE) while satisfying the reliability constraint defined as the Loss of Power Supply Probability (LPSP), below 4%. The results demonstrated that the PV/Wind/BESS configuration exhibited the lowest LCOE at $ \$ $0.014/kWh; 13.6% and 46.2% lower than the PV/BESS and PV/BESS/DG configurations, respectively. Although the PV/BESS/DG scenario demonstrated greater reliability compared to other cases, it incurred the highest LCOE over the project lifetime, which was attributed to volatile fuel prices and elevated operational costs. Furthermore, the sensitivity analysis highlighted the substantial influence of life-cycle costs, including component replacement and operational maintenance costs, on the long-term economic viability of the proposed microgrid configurations. These insights offer valuable strategic guidance for energy policymakers aiming to enhance energy security and autonomy in rural and underserved communities.

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