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Multi‐criteria algorithm‐based methodology used to select suitable domes for compressed air energy storage
Author(s) -
Llamas Bernardo,
Castañeda Maria de la Cruz,
Laín Carlos,
Pous Juan
Publication year - 2017
Publication title -
international journal of energy research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.808
H-Index - 95
eISSN - 1099-114X
pISSN - 0363-907X
DOI - 10.1002/er.3771
Subject(s) - compressed air energy storage , weighting , schedule , analytic hierarchy process , selection (genetic algorithm) , process (computing) , table (database) , salt dome , mathematical optimization , energy storage , reliability engineering , energy consumption , algorithm , computer science , operations research , engineering , data mining , mathematics , machine learning , power (physics) , physics , medicine , paleontology , electrical engineering , quantum mechanics , biology , radiology , operating system
Summary Storing energy allows both the efficiency and availability of renewable energy to be increased, thus dissociating actual from expected generation and from consumption demands. Compressed air energy storage (hereinafter ‘CAES’) enables the efficient and cost‐effective storage of large amounts of energy, achieving a capacity of over 100 MWh. There are several geological structures that can be used as CAES, among which the use and construction of salt domes are particularly noteworthy. However, there is a high exploration risk associated with subsurface exploration. To this end, it is advisable to establish a detailed schedule to select and characterize structures, with the purpose of minimizing the aforementioned risk. Multi‐criteria algorithms can be used to establish a hierarchy of the alternatives and to identify the structures with the greatest potential with an objective approach. The analytic hierarchy process method is used in this paper as the selection algorithm, which is based on identifying and assessing criteria and weighting each criterion. In accordance with the analytic hierarchy process method, the goal was divided into a series of different level criteria, defining a breakdown structure of the problem to select salt domes. This paper defines a structure hierarchization method that allows the objective establishment of the areas with the highest potential for CAES, considering both technical and socioeconomic factors. Therefore, a supporting decision‐making method may be established to reduce the exploration risk associated with underground structures. Copyright © 2017 John Wiley & Sons, Ltd.