Methods to estimate the industrial waste heat potential of regions – A categorization and literature review

Abstract

To investigate heat demand, one can usually base the estimation on sales data for the energy carriers or even use the data directly. This works for companies, regions, towns and sectors (e.g.,industry or domestic sector). But for the waste heat produced by the industry it is not that simple: waste heat is an output value, which neither costs nor earns any money and it is therefore seldom measured or reported. In this paper, different methods to estimate the excess heat of industrial production within a region are categorized and compared. Besides the obviously necessary distinction between theoretical, technical and economic potential, the authors suggest categorization of the methods in three dimensions: study scale, data collection and approach / perspective (bottom up vs. top down). Following this schematic, previous regional waste heat studies are reviewed. Studies focusing on single sectors or companies are not considered in this review, as well as studies estimating the heat demand. As a result it can be seen that the available data are the driving force in the choice for the used estimation method. For general factors, the resulting waste heat potential ranges between 5 and 30% of the energy demand of the industrial sector of a region.Once derived, key figures are often reused in other studies for other countries. Therefore, more data and a thorough metastudy of the available figures aredesirable.

Sarah Brückner would like to thank Stiftung der Deutschen Wirtschaft for her research fellowship. Laia Miró would like to thank the Spanish Government for her research fellowship (BES-2012-051861). The work was partially funded by BMWi Federal Ministry for Economic Affairs and Energy, Germany (Project FKZ 0327383B Mobile Sorption Heat Storage) and the Spanish Government (Project ENE2011-22722). The authors would also like to thank the Catalan Government for the quality accreditation given to their Research group GREA (2009 SGR 534).