Forecast-integrated techno-economic optimization of off-grid hybrid renewable system in hyper-arid regions: Application to Tamanrasset, Algeria

Hadda Zereg and Hassen Bouzgou

Energy, 2025, vol. 334, issue C

Abstract: This study presents a novel framework for the optimal design of an off-grid residential energy system, applied to the hyper-arid region of Tamanrasset, Algeria. The proposed hybrid renewable energy system (HRES) integrates photovoltaic panels, wind turbines, battery storage, and diesel generators. A key innovation is the integration of a green energy forecasting module within a multi-objective techno-economic optimization process. Various machine learning and deep learning models suited for time series prediction were evaluated, and the best-performing models for each meteorological parameter were selected which enables precise long-term hourly forecasts, improving system design and operational efficiency compared to conventional methods based on historical averages. The optimization targets three objectives: minimizing the Levelized Cost of Energy (LCOE), reducing the Loss of Power Supply Probability (LPSP), and maximizing the Reliability Factor (RF). Using the Multi-Objective Particle Swarm Optimization (MOPSO) algorithm, the system achieves an LCOE of $0.05433/kWh, an LPSP of 3.1 %, and an RF of 98 %, indicating a strong balance between cost and reliability. Energy contributions are 47 % from solar PV, 35 % from batteries, 12 % from wind, and 6 % from diesel. Comparison with HOMER Pro simulations confirms the superior economic performance of the MOPSO-based configuration. Sensitivity analyses underscore the critical role of forecast accuracy in HRES performance, while environmental assessments show an 80 % reduction in CO2 emissions compared to diesel-only systems. The integrated forecasting module serves as a valuable decision-support tool for rural electrification, particularly in resource-constrained and climate-challenged regions.

Keywords: Hybrid renewable energy system; Rural electrification; Green energy forecasting; Hyper-arid; Multi-objective optimization; Techno-economic analysis; Algeria (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S036054422503110X
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:334:y:2025:i:c:s036054422503110x

DOI: 10.1016/j.energy.2025.137468

Access Statistics for this article

Energy is currently edited by Henrik Lund and Mark J. Kaiser

More articles in Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().