Techno-economic and Environmental Analysis of Hybrid Energy System (HES) in an Isolated Area

Authors

  • Faqih Abdillah Arif Politeknik Negeri Ujung Pandang, Makassar, Indonesia
  • Dharma Aryani Politeknik Negeri Ujung Pandang, Makassar, Indonesia
  • Ahmad Rosyid Idris Politeknik Negeri Ujung Pandang, Makassar, Indonesia
  • Usman Usman Politeknik Negeri Ujung Pandang, Makassar, Indonesia
  • Ahmad Sabirin Zoolfakar School of Electrical Engineering, College of Engineering, Universiti Teknologi MARA, Selangor, Malaysia
  • Prasad Kaparadju School of Engineering and Built Environment, Griffith University, Brisbane, Queensland, Australia

DOI:

https://doi.org/10.31963/intek.v12i2.5677

Abstract

This study aims to identify the most efficient hybrid energy system configuration from a techno-economic and environmental perspective in an isolated area. The existing system of electrification in remote areas that still rely on diesel power plants incurs high operational costs and produces significant carbon emissions. As a solution, a Hybrid Energy System (HES) integrating solar power plants, diesel power plants, and battery energy storage systems (BESS). The study analyzes the HES configuration on Kodingareng Island using HOMER Pro software. The parameter configuration includes 2024 electricity demand, technical specifications from power plant nameplates, diesel power plant-related data, and market-based estimates for other components. Simulation results show that the optimized system achieves a Net Present Cost (NPC) that is Rp6.76 billion lower than the existing system, with the difference increasing to IDR 8.5 billion when emission penalties are considered. The Levelized Cost of Energy (LCOE) for the optimized system is Rp322.23/kWh lower than the existing configuration, and with emission penalties, the savings increase to Rp405.77/kWh. These findings highlight the potential of HES to reduce costs and emissions in the electrification of remote islands.

Author Biography

Dharma Aryani, Politeknik Negeri Ujung Pandang, Makassar, Indonesia

Modeling & System identification Model Predictive Control Model Based Control Data Based Control Process control SCOPUS ID: 35182491300 https://www.scopus.com/authid/detail.uri?authorId=35182491300 Google Scholars: https://scholar.google.com/citations?user=1yr1u8oAAAAJ&hl=en SINTA: http://sinta2.ristekdikti.go.id/authors/detail?id=6003713&view=overview  

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Published

2025-10-31

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