# Optimizing Sustainable Energy Transitions in Small Isolated Grids Using Multi-Criteria Approaches
## 1 Introduction
### Research Organization and Major Contributions  
Despite preliminary projections of EL Hierro's hydro-wind plant being expected to cover nearly 75% of its energy needs, the system has fallen short of this target. Over nearly a decade of operation, diesel generation has consistently accounted for approximately 50% of electricity production in the hydro-wind facility [25]. A key innovation of this document is the analysis of system sizing to ensure that energy generation is predominantly based on renewables while maintaining high reliability under the various operating conditions that may arise throughout the year. Statistical methods, particularly multi-criteria optimization techniques, have been employed for resource characterization and system optimization. The main optimization criteria include economic viability and the penalization of GHG emissions, as well as constraints related to land use due to the presence of protected areas. Additional limitations concerning the maximum installable capacity of certain technologies have also been considered. For instance, the maximum allowable capacity of solar photovoltaic (PV) systems for self-consumption has been evaluated to prevent excessive visual impact from solar plants or pumped hydro storage facilities. This assessment also considersthe ranges of output power variation and capacity availability, ensuring a balanced and sustainable approach to system design. It should also be highlighted that although the methodology has been applied to a specific case, it could be adapted to any other case. Moreover, the findings presented can be considered almost directly applicable to other cases of small and isolated network systems, as they generally tend to exhibit similar generation typologies as well as the same typical constraints/advantages (limited space, need for reliability, predictability, abundance of resources, etc.). To carry out these calculations, this document presents a novel approach to redesigning energy systems for full renewable energy integration while ensuring reliability under diverse operating conditions. Managing the EPLANopt model linked with EnergyPLAN tool, this study employs multi-objective optimization to identify the ideal resources and their optimal configurations, specifically for isolated regions. Integrating EPLANopt, which uses a Multi-Objective Evolutionary Algorithm (MOEA), with EnergyPLAN's deterministic hourly simulation model allows for a comprehensive exploration of energy system optimization. The EPLANopt model enables the simultaneous optimization of conflicting objectives, such as minimizing costs and CO\({}_{2}\) emissions, yielding a set of trade-offs known as the Pareto front. Constraints like maximum installation capacities for technologies (e.g., rooftop solar to limit visual pollution) and storage parameters (e.g., power and capacity variations) are also factored into the analysis. This combined approach offers an innovative pathway for designing efficient, sustainable energy systems. Through this multi-criteria analysis, the optimal system configuration was determined by considering two main constraints: economic viability and GHG emissions associated with the system throughout its lifecycle. While similar analyses have been conducted by other authors--sometimes using the same variables or including other factors such as energy surpluses--this study stands out by translating the lifecycle emissions of each technology into direct economic terms. This approach provides updated cost figures for the electrical system that fully incorporate emission costs, representing a methodological advance not commonly found in the literature, especially when applied to highly isolated and small-scale systems where reliability is critical. Furthermore, this study includes projections of how varying emission costs could affect overall system expenses. This transformation is particularly significant because, in most cases, major shifts in energy generation are implemented primarily when they become economically viable.