# Optimizing Sustainable Energy Transitions in Small Isolated Grids Using Multi-Criteria Approaches
## 4 Results and Discussion
### Discussion and Major Findings
#### 4.5.1 Synthesis of Essential Aspects in This Study  
Fully renewable energy systems encounter intrinsic challenges in matching financial, ecological, and operating factors. By optimizing storage solutions and integrating a combination of renewable and dispatchable generation sources, it is feasible to design systems that meet multi-criteria optimization objectives. This approach provides a sustainable route to energy self-sufficiency for autonomous systems like El Hierro while also reducing their environmental footprint. However, due to the island's isolation, these must also ensure its self-sufficiency and the ability to meet all its energy demands. Based on the studies conducted, several key aspects can be highlighted:  
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 MW 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:  
1. 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. 2. 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 ensuresa 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.