Optimizing Sustainable Energy Transitions in Small Isolated Grids Using Multi-Criteria Approaches
Abstract
1. Introduction
1.1. Global Energy Transitional Scenario
1.2. Modeling and Optimization—Tools and Techniques
1.3. Research Organization and Major Contributions
2. The Electric System of El Hierro
2.1. The Electric Demand
2.2. The Generation System
2.2.1. The Diesel Generation Plant
2.2.2. The Hydro–Wind Power Plant
3. Materials and Methods
3.1. EnergyPLAN Software
3.2. Optimization Procedures of Multi-Objective Problems
3.3. Definition of Scenarios
- Generation completely based on the diesel thermal power plant (generation systems up to 2014).
- Integrated wind generation with energy storage, alongside a diesel thermal power plant (current generation system).
- Optimizing the configuration of these renewable systems to achieve generation levels as close as possible to a full renewable energy system while considering existing constraints.
4. Results and Discussion
4.1. Scenarios Pre- and Post-Full Operation of the Hydro–Wind Power Plant
4.2. Multi-Objective Optimization
4.3. Collapsing on a Single Optimization Metric
4.4. Performance of the Optimized Generation System
4.5. Discussion and Major Findings
4.5.1. Synthesis of Essential Aspects in This Study
- 1.
- Current Model Validation
- The validation process has confirmed that the model successfully replicates the operational performance of El Hierro’s current energy systems. While minor discrepancies are observed in the hourly values, the overall trends and contributions from the different subsystems are well aligned. This validation demonstrates that the model is suitable for further analysis.
- 2.
- Fossil-Fuel-Based Systems
- Fossil-fuel-dependent systems are characterized by the absence of energy surpluses, as all generations are fully dispatchable. However, this reliability comes at the expense of significantly higher GHG emissions. El Hierro’s energy systems consisted of diesel generators (13 MW) up to 2014.
- 3.
- Evaluation of Current Non-Optimized Renewable System of El Hierro
- The integration of the hydro–wind system on El Hierro has enabled a shift toward renewable energy, but challenges persist due to system over-sizing and continued reliance on fossil-fuel backup. The current energy setup combines diesel generators (13 MW) with a hydro–wind system (11.5 MW wind, 6 MW pumping power, 11.25 MW turbination power, and 225 MWh storage). The hydro–wind plant enhances flexibility by managing wind power surplus, reducing surplus generation. However, diesel backup is still necessary when renewable energy is lacking, contributing to GHG emissions.
- 4.
- Multi-Criteria Optimization Analysis
- A multi-criteria optimization framework was used to design energy systems that minimize costs and emissions while balancing these factors. The analysis highlights the need for a primarily renewable system with moderate dispatchable generation, which could include biomass or geothermal sources if available. Expanding storage capacities, such as BESS or CAES, could address energy shortfalls. A balanced installed power of solar and wind generation (close to current wind capacity), in addition to an increased reversible pumping storage capacity (somewhat more than double the current level), while preserving the powers of pumping and turbination, with a significant diesel capacity (roughly equal to peak demand) would continue as a backup system, contributing about 10% of the overall generation.
- 5.
- Drawbacks of Optimized Systems based on Non-Dispatchable Resources
- The performance of renewable energy systems varies significantly over the years due to resource variability and unpredictability, especially when storage is limited. Two main options for system dimensioning:
- System sizing is based on the worst-case renewable resource year. In favorable years, renewable energy generation largely exceeds demand, leading to significant energy surpluses and reduced need for backup systems.
- System sizing is based on the average-case renewable resource year. In unfavorable years, renewable energy generation is largely lacking, leading to substantial use for backup systems.
- 6.
- Fully Renewable Systems
- Transitioning to an entirely renewable energy system requires over-dimensioning of generation and storage to account for the variability in renewable resources. This ensures a reliable energy supply during periods of low generation. While necessary for energy security, over-dimensioning increases costs due to the need for additional capacity and infrastructure.
- Challenges for system over-dimensioning: excess renewable capacity can result in energy excesses, economic ineffectiveness, and environmental impacts, especially when storage options are restricted.
- Importance of large-scale storage: sufficient storage solutions (e.g., pumped hydro, CAES, large BESS) can help manage energy surpluses, but their implementation is often constrained by geographical, technical, and economic factors.
- Need for backup systems: fundamental in coupling generation and demand in renewable energy systems due to their intermittent nature. The following are viable options:
- -
- Fossil fuel backup systems: while reliable and cost-effective, fossil fuels are unsustainable due to their high GHG emissions.
- -
- Renewable backup systems: options such as geothermal and biomass have reduced GHG emissions but face challenges related to resource availability, elevated costs and operational complexities.
4.5.2. Fundamental Insights for Improving Renewable Generation Integration
- -
- Decarbonization challenges: Transitioning to renewable energy faces challenges due to the current heavy reliance on fossil fuels. Wind and solar are intermittent, which makes it difficult to ensure a stable energy supply, particularly in isolated regions without connections to larger grids.
- -
- Isolated regions’ issues: Islands and remote regions face additional difficulties because they must be self-sufficient. They rely on fossil fuels for their stability, as renewables alone cannot always meet their energy needs.
- -
- Renewable energy and storage needs: To support decarbonization, large-scale renewable energy generation is necessary, but storage is essential to bridge gaps during times of low renewable generation, ensuring a reliable power supply.
- -
- EnergyPLAN Tool: The EnergyPLAN software was used to simulate various renewable energy system scenarios. It helps analyze different configurations by modeling energy systems’ performance in terms of energy balance, reliability, and economic impact.
- -
- Optimization technique: A multi-objective optimization technique was employed to balance system costs and GHG emissions, taking into account system constraints such as technology capacities and storage. This approach optimizes the energy system for both cost-effectiveness and environmental impact. The NSGA-II algorithm was selected for the optimization process, as it has demonstrated strong performance and yielded results comparable to those of other commonly used algorithms [43].
- -
- El Hierro case study: The optimization technique was applied to El Hierro, which has an existing renewable energy system. This case study highlights the system’s performance and the potential for improvement, showing a hybrid hydro–wind system with significant diesel reliance.
- -
- Adverse conditions and system design: in years with poor renewable resource conditions (e.g., 2023), the renewable system could only cover 35% of the demand, indicating that system designs must account for low generation periods, still relying on diesel generation.
- -
- Excess generation in favorable years: while renewable energy systems show surplus generation during favorable years (30–50%), this excess energy represents inefficiencies. A 100% renewable system would require significant over-sizing of both generation and storage.
- -
- Renewable backup alternatives: To fully eliminate diesel, alternatives like biomass or geothermal would be necessary. However, their availability is limited, especially on islands like El Hierro, where imports would be required, adding complexity and cost.
- -
- Optimized system design: the proposed optimized system reduces diesel use, adds more solar capacity, and increases storage, cutting emissions by 75% and reducing costs by one-third compared to the current system.
- -
- Pathway to decarbonization: Achieving full decarbonization requires careful system planning and optimization. Without it, oversizing systems could lead to wasted resources, making it crucial to select the right path to reach sustainable energy goals, especially in isolated regions.
5. Conclusions
- -
- Diesel-based systems are cost-effective but environmentally harmful, and they remain essential in small-scale networks until renewable infrastructure is fully developed.
- -
- Fossil fuels may act as transitional backups in renewable systems due to the unpredictability of wind and solar energy.
- -
- Islands and remote regions face greater reliance on fossil fuels or large storage due to lack of grid connections.
- -
- The most used sustainable renewable backup options, biomass and geothermal, are often unavailable, leading to more fossil fuel dependence.
- -
- There is a need to promote other renewable backup energies, like solar thermal energy, micro-hydropower, tidal and wave energy, to avoid using fossil-fuel-based systems.
- -
- Relying on a single renewable backup source is difficult due to variability, geographic limits, and infrastructure constraints. Using multiple backup systems can fill gaps left by others.
- -
- Large-scale energy storage is fundamental but economically challenging due to high costs.
- -
- Oversizing renewable systems can reduce emissions but create inefficiencies, making storage vital for balancing supply and demand.
- -
- GHG penalties are necessary to phase out fossil-fuel-based systems, but significant taxes are required to make renewable solutions economically viable.
- -
- Policies should balance emissions reduction and storage investments to ensure an efficient and sustainable energy transition.
Author Contributions
Funding
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Year | Demand (GWh) | Diesel (%) | Renewable 1 (%) |
---|---|---|---|
2013 | 44.02 | 99.53% | 0.47% |
2014 | 42.08 | 97.45% | 2.55% |
2015 | 42.99 | 80.10% | 19.90% |
2016 | 44.6 | 59.41% | 40.59% |
2017 | 43.83 | 53.46% | 46.54% |
2018 | 41.93 | 43.58% | 56.42% |
2019 | 42.85 | 45.70% | 54.30% |
2020 | 46.81 | 58.26% | 41.74% |
2021 | 47.92 | 51.82% | 48.18% |
2022 | 47.00 | 51.06% | 48.94% |
2023 | 50.24 | 65.21% | 34.79% |
Production Type | Investment Costs (M EUR/MW) | O&M (%) | Lifetime (Years) |
---|---|---|---|
Diesel power generator 1 | 0.4 | 5 | 20 |
Wind power | 1.32 | 2.97 | 20 |
Hydro turbination | 3 | 1.5 | 50 |
Hydro storage 2 | 7.5 × 10−3 | 1.5 | 50 |
Hydro pump | 0.6 | 2.5 | 30 |
Solar Photovoltaic | 1.3 | 0.27 | 20 |
Generation Technology | Life Cycle Emissions (gCO2eq/kWhe) |
---|---|
Diesel power plant | 795 |
Solar photovoltaic | 40 |
Wind power | 13 |
Pumped storage | 7.4 |
Variable | Results for 2023 | |
---|---|---|
Installed power | 13.04 MW | |
Generation | 50.50 GWh | |
Average CF | 43.97% | |
Peak CF | 59.13% | |
Total annual costs | 6.835 M EUR | |
Fixed operation costs | 0.377 M EUR | 5.52% |
Variable costs | 6.458 M EUR | 94.48% |
Annual investment costs | 0 M EUR | ----- |
GHG emissions | 40.16 kt |
Technology | Results for 2023 Simulation | |
---|---|---|
Diesel power plant | ||
Installed diesel power | 13.04 MW | |
Generation | 31.41 GWh | |
Average CF | 27.50% | |
Peak CF | 59.13% | |
Annual costs | 4.278 M EUR 1 | |
Fixed operation costs | 0.261 M EUR | 6.10% |
Variable costs | 4.017 M EUR | 93.90% |
Annual investment costs | 0 M EUR | ---- |
Hydro–wind plant | ||
Wind | ||
Installed wind power | 11.50 MW | |
Generation | 23.93 GWh | |
Average CF | 23.75% | |
Peak CF | 67.05% | |
Annual costs | 1.471 M EUR 1 | |
Fixed operation costs | 0.45 M EUR | 30.66% |
Annual investment costs 1 | 1.02 M EUR | 69.34% |
Hydro storage | ||
Installed pump power | 6 MW | |
Installed turbine power | 11.30 MW | |
Storage capacity | 225 MWh | |
Energy pumped | 7.52 GWh | |
Hydro pump average CF | 14.31% | |
Hydro pump peak CF | 100% | |
Energy turbinated | 2.78 GWh | |
Turbine average CF | 2.76% | |
Turbine peak CF | 67.05% | |
Annual costs | 2.410 M EUR 1 | |
Fixed operation costs | 0.685 M EUR | 28.42% |
Annual investment costs1 | 1.725 M EUR | 71.58% |
Total annual costs | 8.159 M EUR | |
GHG emissions | 24.063 kt |
Technology | Results for Optimal Setup | |
---|---|---|
Diesel power plant | ||
Installed diesel power | 9 MW | |
Generation | 7.35 GWh | |
Average CF | 9.33% | |
Peak CF | 85.67% | |
Annual costs | 1.187 M EUR 1 | |
Fixed operation costs | 0.180 M EUR | 20.58% |
Variable costs | 1.007 M EUR | 79.42% |
Annual investment costs | 0 M EUR | -% |
Wind–hydro plant | ||
Wind | ||
Installed wind power | 11.50 MW | |
Generation | 25.48 GWh | |
Average CF | 24.65% | |
Peak CF | 65.34% | |
Annual costs | 1.51 M EUR 1 | |
Fixed operation costs | 0.463 M EUR | 30.66% |
Annual investment costs 1 | 1.047 M EUR | 69.34% |
Hydro storage | ||
Installed pump power | 7.2 MW | |
Installed turbine power | 11.3 MW | |
Storage capacity | 500 MWh | |
Energy pumped | 16.64 GWh | |
Hydro pump average CF | 26.38% | |
Hydro pump peak CF | 100% | |
Energy turbinated | 8.37 GWh | |
Turbine average CF | 8.10% | |
Turbine peak CF | 65.34% | |
Annual costs | 2.628 M EUR 1 | |
Fixed operation costs | 0.749 M EUR | 28.50% |
Annual investment costs 1 | 1.879 M EUR | 71.50% |
Solar PV | ||
Installed Power | 13.30 MW | |
Generation | 27.36 GWh | |
Average CF | 23.48% | |
Peak CF | 57.97% | |
Annual costs | 1.266 M EUR 1 | |
Fixed operation costs | 0.104 M EUR | 8.21% |
Annual investment costs 1 | 1.162 M EUR | 91.79% |
Total annual costs | 6.591 M EUR | |
GHG emissions | 6.26 kt |
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Berna-Escriche, C.; Álvarez-Piñeiro, L.; Blanco, D.; Rivera, Y. Optimizing Sustainable Energy Transitions in Small Isolated Grids Using Multi-Criteria Approaches. Appl. Sci. 2025, 15, 7644. https://doi.org/10.3390/app15147644
Berna-Escriche C, Álvarez-Piñeiro L, Blanco D, Rivera Y. Optimizing Sustainable Energy Transitions in Small Isolated Grids Using Multi-Criteria Approaches. Applied Sciences. 2025; 15(14):7644. https://doi.org/10.3390/app15147644
Chicago/Turabian StyleBerna-Escriche, César, Lucas Álvarez-Piñeiro, David Blanco, and Yago Rivera. 2025. "Optimizing Sustainable Energy Transitions in Small Isolated Grids Using Multi-Criteria Approaches" Applied Sciences 15, no. 14: 7644. https://doi.org/10.3390/app15147644
APA StyleBerna-Escriche, C., Álvarez-Piñeiro, L., Blanco, D., & Rivera, Y. (2025). Optimizing Sustainable Energy Transitions in Small Isolated Grids Using Multi-Criteria Approaches. Applied Sciences, 15(14), 7644. https://doi.org/10.3390/app15147644