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Decision Support System of Innovative High-Temperature Latent Heat Storage for Waste Heat Recovery in the Energy-Intensive Industry

doi: 10.3390/en14020365
Reductions in energy consumption, carbon footprint, equipment size, and cost are key objectives for the forthcoming energy-intensive industries roadmaps. In this sense, solutions such as waste heat recovery, which can be replicated into different sectors (e.g., ceramics, concrete, glass, steel, aluminium, pulp, and paper) are highly promoted. In this line, latent heat thermal energy storage (TES) contributes as an innovative technology solution to improve the overall system efficiency by recovering and storing industrial waste heat. To this end, phase-change material (PCM) selection is assisted through a decision-support system (DSS). A simplified tool based on the MATLAB® model, based on correlations among the most relevant system parameters, was developed to prove the feasibility of a cross-sectorial approach. The research work conducted a parametric analysis to assess the techno-economic performance of the PCM-TES solution under different working conditions and sectors. Additionally, a multicriteria assessment was performed comparing the tool outputs from metal alloys and inorganic hydrated PCM salts. Overall, the inorganic PCMs presented higher net economic and energy savings (up to 25,000 €/yr; 480 MWh/yr), while metal alloys involved promising results, shorter cycles, and competitive economic ratios; its commercial development is still limited.
- University of Zaragoza Spain
waste heat recovery, Technology, multicriteria analysis, decision support system, energy-intensive industry, T, thermal energy storage, system integration, phase change materials
waste heat recovery, Technology, multicriteria analysis, decision support system, energy-intensive industry, T, thermal energy storage, system integration, phase change materials
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).21 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10% visibility views 3 download downloads 7 - 3views7downloads
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