Uncovering relationships between environmental metrics in the multi-objective optimization of energy systems: A case study of a thermal solar Rankine reverse osmosis desalination plant
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Date
2013
Authors
Antipova, Ekaterina
Boer, Dieter
Cabeza, Luisa F.
Guillén Gosálbez, Gonzalo
Jiménez Esteller, Laureano
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Abstract
Multi-objective optimization (MOO) is increasingly being used in a wide variety of applications to
identify alternatives that balance several criteria. The energy sector is not an exception to this trend.
Unfortunately, the complexity of MOO grows with the number of environmental objectives. This limitation
is critical in energy systems, in which several environmental criteria are typically used to assess
the merits of a given technology. In this paper, we investigate the use of a rigorous dimensionality
reduction method for reducing the complexity of MOO as applied to an energy system (i.e., a solar
Rankine cycle coupled with reverse osmosis and thermal storage). Instead of using an aggregated
environmental metric, a common approach for reducing the number of environmental objectives in
MOO, we propose to optimize the system in a reduced search space of objectives that fully describe its
performance and which results from eliminating redundant criteria from the analysis. Numerical results
show that it is possible to reduce the problem complexity by omitting redundant environmental indicators
from the optimization.
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Energy, 2013, núm. 51, p. 50-60