The recovery and utilisation of industrial excess heat has been identified as an important contribution for energy efficiency by reducing primary energy demand. Previous works, based on top-down studies for a few sectors, or regional case studies estimated the overall availability of industrial excess heat. A more detailed analysis is required to allow the estimation of potentials for specific heat recovery technologies, particularly regarding excess heat temperature profiles. This work combines process integration methods and regression analysis to obtain cogeneration targets, detailed excess heat temperature profiles and estimations of electricity generation potentials from low and medium temperature excess heat. The work is based on the use of excess heat temperature (XHT) signatures for individual sites and regression analysis using publicly available data, obtaining estimations of the technical potential for electricity generation from low and medium temperature excess heat (60–140 °C) for the whole Swedish kraft pulp and paper industry. The results show a technical potential to increase the electricity production at kraft mills in Sweden by 10 to 13%, depending on the level of process integration considered, and a lower availability of excess heat than previously estimated in studies for the sector. The approach used could be adapted and applied in other sectors and regions, increasing the level of detail at which industrial excess heat estimations are obtained when compared to previous studies.
Increasing energy efficiency within the industrial sector is one of the main approaches in order to reduce global greenhouse gas emissions. The production and processing of aluminium is energy and greenhouse gas intensive. To make well-founded decisions regarding energy efficiency and greenhouse gas mitigating investments, it is necessary to have relevant key performance indicators and information about energy end-use. This paper develops a taxonomy and key performance indicators for energy end-use and greenhouse gas emissions in the aluminium industry and aluminium casting foundries. This taxonomy is applied to the Swedish aluminium industry and two foundries. Potentials for energy saving and greenhouse gas mitigation are estimated regarding static facility operation. Electrolysis in primary production is by far the largest energy using and greenhouse gas emitting process within the Swedish aluminium industry. Notably, almost half of the total greenhouse gas emissions from electrolysis comes from process-related emissions, while the other half comes from the use of electricity. In total, about 236 GWh/year (or 9.2% of the total energy use) and 5588–202,475 tonnes CO2eq/year can be saved in the Swedish aluminium industry and two aluminium casting foundries. The most important key performance indicators identified for energy end-use and greenhouse gas emissions are MWh/tonne product and tonne CO2-eq/tonne product. The most beneficial option would be to allocate energy use and greenhouse gas emissions to both the process or machine level and the product level, as this would give a more detailed picture of the company’s energy use and greenhouse gas emissions.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.