Optimal sizing of hybrid energy systems for decarbonization considering demand response and energy storage

Maghami, Mohammad Reza and Pasupuleti, Jagadeesh and Mazlan, Mohamed and Ekanayake, Janaka (2025) Optimal sizing of hybrid energy systems for decarbonization considering demand response and energy storage. Energy Conversion and Management: X, 28 (101250). pp. 1-18. ISSN 2590-1745

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Abstract

Designing cost-effective and low-emission Hybrid Energy Systems (HES) for off-grid rural areas requires not only optimal sizing but also a strong understanding of how key parameters impact system performance. In this study, sensitivity analysis is a central component, used to evaluate the effects of varying capital costs, battery capacity, Demand Response (DR) parameters, Diesel Generator (DG) size, and Renewable Energy Fraction (REF) on both economic and environmental outcomes. This approach ensures that the most robust and resilient configuration is identified under changing technical and financial conditions. A rural village in South Khorasan, Iran, with a daily load demand of 68 kWh, was selected as the case study. Four system configurations were simulated using HOMER Pro and MATLAB: (1) base HES, (2) HES with DR, (3) HES with DG, and (4) HES with both DR and DG. The results show that Scenario 4 (HES + DR + DG) provided the best performance. It reduced the Cost of Energy (COE) by 17 % (from $0.392/kWh to $0.328/kWh) and the Net Present Cost (NPC) by 16 % (from $124,780 to $104,706). The system achieved an 88 % RF, while DG operation was limited to 1831 h per year with 1108 L of fuel consumed. DR implementation also reduced battery size requirements by 37 %. This study demonstrates that integrating DR and DG, guided by detailed sensitivity analysis, leads to an optimized, low-emission, and cost-efficient HES suitable for rural electrification.

Item Type:	Article
Uncontrolled Keywords:	Hybrid Energy System, Demand Response, Battery Energy Storage, Diesel generator, RF and Decarbonization
Divisions:	Faculty of Artificial Intelligence and Cyber Security
Depositing User:	Norfaradilla Idayu Ab. Ghafar
Date Deposited:	13 Apr 2026 08:09
Last Modified:	13 Apr 2026 08:09
URI:	http://eprints.utem.edu.my/id/eprint/29666
Statistic Details:	View Download Statistic

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