A review of multi-criteria decision making approaches for evaluating energy storage systems for grid applications
2019
Energy storage systems (ESS) are seen as one of the main pillars for a renewable-based energy system. Selecting the most suitable and sustainable ESS for a given project is a problem that involves multiple stakeholders with quite often diverging objectives that cannot all be fulfilled by a single technology. Several studies are available that tackle this problem applying multi-criteria decision analysis (MCDA). However, these use very different Multi-Attribute Decision Making (MADM) approaches, criteria and goals for decision support, why their results are difficult to compare or to reproduce. This work presents a review of existing MCDA-literature using MADM as a tool for sustainability evaluation of grid-tied ESS. Available studies are summarized, the goals, used MADM methods, and quantification of criteria are analyzed and discussed to provide tentative recommendations. The reviewed studies cover multiple technologies ranging from electrochemical, mechanical or electric ESS. Considered criteria are mainly structured around technology, economy, society, and environment, comprising a high number of individual sub-criteria. The aggregation of these criteria is mainly realized through the Analytic Hierarchy Process (AHP) in combination with a wide set of other methods. The quantification of various criteria is often based on different literature sources wherein context-free data for cost, and environmental impacts are used, leading in some cases to inconsistent comparisons in the assessments. Only in a few cases, assessments are linked to specific application requirements, which are decisive factors for the design of an ESS. A minority of the reviewed works include a representative set of decision-makers in their approaches, wherein the number or type of participants is often not communicated transparently. Therefore, most of the studies are considered to have a limited orientation towards practical decision making, but they provide valuable information regarding MADM method development.
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