Page 293 - Materials Chemistry, Second Edition

292 14. LCS prioritization of energy storage under uncertainties

been deployed in the renewable energy-based electric power system. However, how to select
the most suitable electrochemical energy storage is a practical and vital issue for electric
power operators and planners. Different electrochemical energy storage systems have vari-
ous characteristics regarding life time, power rating, discharge time, and energy density, and
one kind of electrochemical energy storage may have an advantage related to one criterion
but may be weak on other criteria. So, the prioritization and selection of electrochemical en-
ergy storage can be classified as a multi-criteria decision-making (MCDM) issue, including
various conflicting criteria.
Currently, there are many MCDM methods, such as AHP, TOPSIS, matter-element exten-
sion model, grey relation decision-making, and best-worst method, some of which have been
employed in the prioritization of electrochemical energy storage. Barin et al. (2009) employed
the analytic hierarchy process (AHP) and fuzzy logic to assess the operations of different me-
chanical energy storage systems. Daim et al. (2012) evaluated the priority values of three en-
ergy storage technologies by using fuzzy Delphi, AHP, and fuzzy consistent matrix based on
experts’ judgments. Gumus et al. (2013) developed a new MCDM model based on Buckley
extension fuzzy AHP and linear normalization fuzzy grey relation analysis (GRA) for the se-
lection of Turkey’s hydrogen storage. Ozkan et al. (2015) conducted the evaluation on electric
energy storage based on decision-makers’ opinions and judgments by using AHP and type-2
fuzzy TOPSIS MCDM method.
Ren (2018) proposed a novel intuitionistic fuzzy combinative distance-based assessment
approach for sustainability prioritization of energy storage technologies, which combines in-
terval AHP for criteria weight determination and intuitionistic fuzzy combinative distance-
based assessment method for alternative prioritization. Ren and Ren (2018) performed the
sustainability ranking of energy storage technologies under uncertainties using the non-
linear fuzzy prioritization and interval MCDM method, and the ranking result was compared
with that of interval TOPSIS. Zhao et al. (2018) conducted the comprehensive performance
assessment on various battery energy storage systems using a multi-criteria decision-making
(MCDM) model, in which a fuzzy-Delphi approach was used to establish the comprehensive
assessment indicator system, the entropy weight determination method and the best-worst
method (BWM) were used to calculate weights of all sub-criteria, and a Vlsekriterijumska
Optimizacija I Kompromisno Resenje (VIKOR) used to choose the optimal battery ESS. Zhao
et al. (2019) proposed an integrated MCDM method combining fuzzy-Delphi, best-worst
method, and fuzzy cumulative prospect theory for comprehensive assessment on battery en-
ergy storage systems considering risk preferences of decision-makers.
The above-mentioned studies have provided valuable tools and methods for the selection
of electric energy storage. However, there are still several research gaps, as follows:

(1) The evaluation index system is fragmentary, and mostly focuses on the production stage,
not considering the life cycle sustainability view.
(2) The criteria weight determination rarely considers the opinions of different decision-
makers, and only considers one integrated decision-maker’s judgment.
(3) The prioritization of electrochemical energy storage still lacks consideration of
uncertainties from data collection and decision-making processes.
To tackle these issues, this chapter aims at developing a life cycle sustainability decision-
making framework for the prioritization of electrochemical energy storage under uncer-
tainties. The evaluation criteria are selected from the perspective of life-cycle sustainability,