Techno-economic modelling and optimisation of excess heat and cold recovery for industries: A review
Shravan Kumar,
Jagruti Thakur and
Francesco Gardumi
Renewable and Sustainable Energy Reviews, 2022, vol. 168, issue C
Abstract:
Recovery and use of industrial excess heat and cold are expected to play a huge role in the decarbonisation of heating and cooling systems in Europe. From the perspective of the industry, it could also promote a coupling between the sectors and help offset emissions, leading to a sustainable industry. However, there exists a gap in knowledge regarding the planning of infrastructure for utilization of excess heat, specifically for industries. This study aims at reviewing energy system optimisation tools that can be used by industrial stakeholders to plan energy investments for recovery and utilization of excess heat and cold. Through a study of existing energy systems models, seven tools are found suitable for analysing industrial excess heat and cold recovery. A detailed review of these tools is conducted and they are compared. The capability of the models to represent and analyse industrial excess heat and cold recovery options are critically discussed. The main requirements of such an analysis are used to establish criteria for comparison. The results of the comparison are used as a knowledge base to form a simple decision support tool to help industrial stakeholders choose the most suitable energy system model. The results from the review, comparison and decision support tool indicate that none of the models is capable of fulfilling all needs in every case. They also highlight that the choice of the tool depends especially on the required temporal and spatial resolution and its interoperability.
Keywords: Excess heat and cold; District heating and cooling systems; Energy system model; Industrial heat recovery; Techno-economic optimisation; Heat and cold recovery (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (2)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:rensus:v:168:y:2022:i:c:s1364032122006943
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DOI: 10.1016/j.rser.2022.112811
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