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Article

Forecasting Renewable Scenarios and Uncertainty Analysis in Microgrids for Self-Sufficiency and Reliability: Estimation of Extreme Scenarios for 2040 in El Hierro (Spain)

by
Lucas Álvarez-Piñeiro
1,2,
César Berna-Escriche
1,2,*,
Paula Bastida-Molina
1,3 and
David Blanco-Muelas
1
1
Instituto Universitario de Investigación en Ingeniería Energética, Universitat Politècnica de València (UPV), Camino de Vera 14, 46022 Valencia, Spain
2
Departamento de Estadística, Investigación Operativa Aplicadas y Calidad, Universitat Politècnica de València (UPV), Camino de Vera 14, 46022 Valencia, Spain
3
Departamento de Ingeniería Eléctrica, Universitat Politècnica de València (UPV), Camino de Vera s/n, 46022 Valencia, Spain
*
Author to whom correspondence should be addressed.
Appl. Sci. 2025, 15(21), 11815; https://doi.org/10.3390/app152111815
Submission received: 17 October 2025 / Revised: 30 October 2025 / Accepted: 3 November 2025 / Published: 5 November 2025
(This article belongs to the Special Issue Advanced Forecasting Techniques and Methods for Energy Systems)

Abstract

This study evaluates the feasibility of fully renewable energy systems on El Hierro, the smallest and most isolated Canary Archipelago Island (Spain), contributing to the broader effort to decarbonize the European economy. By 2040, the island’s energy demand is projected to reach 80–110 GWh annually, assuming full economic decarbonization. Currently, El Hierro faces challenges due to its dependence on fossil fuels and inherent variability of renewable sources. To ensure system reliability, the study emphasizes the integration of renewable and storage technologies. Two scenarios are modeled using HOMER Pro 3.18.4 software with probabilistic methods to capture variability in generation and demand. The first scenario, BAU, represents the current system enhanced with electric vehicles. While the second, Efficiency, incorporates energy efficiency improvements and collective mobility policies. Both prioritize electrification and derive an optimal generation mix based on economic and technical constraints, to minimize Levelized Cost Of Energy (LCOE). The approach takes advantage of El Hierro’s abundant solar and wind resources, complemented by reversible pumped hydro storage and megabatteries. Fully renewable systems can meet demand reliably, producing about 30% energy surplus with an LCOE of roughly 10 c€/kWh. The final BAU scenario includes 53 MW of solar PV, 16 MW of wind, and a storage system of 40 MW–800 MWh. The Efficiency scenario has 42 MW of solar PV, 11.5 MW of wind, and 35 MW–550 MWh of storage. Uncertainty analysis indicates that maintaining system reliability requires an approximate 10% increase in both installed capacity and costs. This translates into an additional 7 MW of solar PV and 6 MW–23.5 MWh of batteries in the BAU, and 6 MW and 4 MW–16 MWh in the Efficiency.
Keywords: uncertainty analysis; Best Estimate Plus Uncertainty (BEPU) analysis; Wilks formula; energy balance forecasts; Hybrid Renewable Energy System; sustainable energy transition uncertainty analysis; Best Estimate Plus Uncertainty (BEPU) analysis; Wilks formula; energy balance forecasts; Hybrid Renewable Energy System; sustainable energy transition

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MDPI and ACS Style

Álvarez-Piñeiro, L.; Berna-Escriche, C.; Bastida-Molina, P.; Blanco-Muelas, D. Forecasting Renewable Scenarios and Uncertainty Analysis in Microgrids for Self-Sufficiency and Reliability: Estimation of Extreme Scenarios for 2040 in El Hierro (Spain). Appl. Sci. 2025, 15, 11815. https://doi.org/10.3390/app152111815

AMA Style

Álvarez-Piñeiro L, Berna-Escriche C, Bastida-Molina P, Blanco-Muelas D. Forecasting Renewable Scenarios and Uncertainty Analysis in Microgrids for Self-Sufficiency and Reliability: Estimation of Extreme Scenarios for 2040 in El Hierro (Spain). Applied Sciences. 2025; 15(21):11815. https://doi.org/10.3390/app152111815

Chicago/Turabian Style

Álvarez-Piñeiro, Lucas, César Berna-Escriche, Paula Bastida-Molina, and David Blanco-Muelas. 2025. "Forecasting Renewable Scenarios and Uncertainty Analysis in Microgrids for Self-Sufficiency and Reliability: Estimation of Extreme Scenarios for 2040 in El Hierro (Spain)" Applied Sciences 15, no. 21: 11815. https://doi.org/10.3390/app152111815

APA Style

Álvarez-Piñeiro, L., Berna-Escriche, C., Bastida-Molina, P., & Blanco-Muelas, D. (2025). Forecasting Renewable Scenarios and Uncertainty Analysis in Microgrids for Self-Sufficiency and Reliability: Estimation of Extreme Scenarios for 2040 in El Hierro (Spain). Applied Sciences, 15(21), 11815. https://doi.org/10.3390/app152111815

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