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Title:
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Enhanced thermal energy supply via central solar heating plants with seasonal storage: A multi-objective optimization approach
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Author:
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Tulus, Victor; Boer, Dieter; Cabeza, Luisa F.; Jiménez, Laureano; Guillén Gosálbez, Gonzalo
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Notes:
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Central solar heating plants with seasonal storage (CSHPSS) are among the most promising technologies to save energy in the industrial and residential-commercial building sectors. This work introduces a systematic approach to optimize these systems according to economic and environmental criteria. Our method, which combines the TRNSYS 17 simulation software with life cycle assessment and multi-objective optimization, identifies optimal CSHPSS designs for any climatic condition and heating demand profile considering economic and environmental criteria simultaneously. The capabilities of this approach are illustrated through its application to a case study of a CSHPSS located in Barcelona (Spain), which satisfies a heating demand for a neighborhood of 1120 dwellings. Numerical results show that the CSHPSS plant leads to significant environmental and economic improvements compared to the use of a conventional natural gas heating system. Our tool can guide engineers and architects in the transition towards a more sustainable residential sector.
The authors would like to acknowledge financial support from the Spanish Government (CTQ2012-37039-C02-01, ENE2015-64117-C5-3-R, ENE2015-64117-C5-1-R, MINECO/FEDER, UE) and to thank the Catalan Government for the quality accreditation given to the research group GREA (2014 SGR 123). The research leading to these results has received funding from the European Commission Seventh Framework Programme under grant agreement no. PIRSES-GA-2013-610692 (INNOSTORAGE). |
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Subject(s):
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-Central solar heating plant with seasonal storage
-Thermal energy storage
-Solar district heating
-Multi-objective optimization
-Life cycle assessment |
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Rights:
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(c) Elsevier, 2016
info:eu-repo/semantics/restrictedAccess |
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Document type:
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article
publishedVersion |
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Published by:
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Elsevier
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