Abstract

This article presents an assessment of the most suitable compressed air energy storage (CAES) reservoirs and facilities to better integrate renewable energy into the electricity grid. The novelty of this study resides in selecting the best CAES reservoir sites through the application of a multi-criteria decision aid (MCDA) tool, specifically the simple additive weighting (SAW) method. Besides using geographic information systems (GIS) spatial representation of potential reservoir areas, for the MCDA method, several spatial criteria, environmental and social constraints, and positive incentives (e.g., the proximity to existing power generation facilities of renewable energy sources) were contemplated. As a result, sixty-two alternatives or potential reservoir sites were identified, and thirteen criteria (seven constraints and six incentives) were considered. The final stage of this study consisted of conducting a sensitivity analysis to determine the robustness of the solutions obtained and giving insights regarding each criterion’s influence on the reservoir sites selected. The three best suitable reservoir sites obtained were the Monte Real salt dome, Sines Massif, and the Campina de Cima—Loulé salt mine. The results show that this GIS-MCDA methodological framework, integrating spatial and non-spatial information, proved to provide a multidimensional view of the potential reservoir CAES systems incorporating both constraints and incentives.

Highlights

  • Portugal has one of the highest shares of renewable energy production within the European Union (EU), with more than half of the electricity consumed in 2019 coming from renewable energy sources (RES)

  • multi-criteria decision aid (MCDA) methods usually resort to sensibility analysis as the last step of evaluation in all decision problems [22] because the majority of data in MCDA problems are unstable and changeable [40], and model outcomes are open to multiple types of uncertainty [41]

  • A “what if” sensibility analysis is recommended to check the stability of results against the subjectivity of the experts [11], explaining how much the decisionmakers judgements bias the assessment of an MCDA study [43]

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Summary

Introduction

Portugal has one of the highest shares of renewable energy production within the European Union (EU), with more than half of the electricity consumed in 2019 coming from renewable energy sources (RES). This study was based on the potential geological sites for large-scale CAES in mainland Portugal obtained from the Energy Storage Mapping and Planning (ESTMAP) studies—an EU Horizon 2020 project—described in [5]. While this latter project focuses on the several possible underground ES technologies available for Europe, the present study explicitly addressed CAES in Portugal, including potential reservoirs not previously considered [5]. A robust assessment of the results found was conducted through a sensibility analysis (SA)

Compressed Air Energy Storage Reservoirs and GIS
Objective
Normalization Process
Absence of constraint
Assigning Weights to the Criteria
Obtaining SAW Results
Sensibility Analysis
Results of the MCDA
Results of the Sensitivity Analysis
Conclusions
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