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ECN publication
Title:
Analysis of energy use and carbon losses in the chemical and refinery industries
 
Author(s):
Bach, P.W.; Haije, W.G.; Neelis, M.L.; Patel, M.K.
 
Published by: Publication date:
ECN Energy Efficiency in Industry 1-9-2005
 
ECN report number: Document type:
ECN-I--05-008 Other
 
Number of pages: Full text:
82 Download PDF  

Abstract:

The chemical and refinery industry are both major consumers of energy. More energy efficient technologies in those industries therefore have the potential to contribute significantly to energy savings and the reduction of CO2 emissions at the macro-economic level. In order to assess these potentials, it is important to have a proper overview of the structure of energy use and CO2 emissions in these industries.

In this study an overview based on a spreadsheet model containing process datasets for 68 production processes for the production of 53 of the most important chemicals in terms of production volume and for 16 of the most important processes in the refinery industry is presented. The model also contains production volumes for the chemicals included and process volumes for the various refinery processes for the Netherlands, Western Europe and the world in 2000. The processes cover approximately 70% of the final energy use in the chemical and refinery industries.

For the processes analysed in the chemical industry, both the heat effects of the chemical reactions and the energy use of the processes are quantified. The sum of both equals the total energy loss of the processes (i.e. the amount of waste heat to the environment).

The total final energy loss in Western Europe for the processes analysed equals 1620 PJf in Western Europe in 2000, the total primary energy loss equals 1894 PJp. Total CO2 emissions are calculated as 111 Mt CO2, assuming steam and electricity to be produced separately (no cogeneration). Three processes (ethylene, ammonia and chlorine production) contribute approximately 50% to the total energy loss.

The ultimate theoretical energy saving potential of the processes is equal to the total energy loss of the process. The processes with large energy losses in relative (in GJ per tonne of product) and absolute terms (in PJ / year) are identified. The energy losses are split into losses due to non-selectivity, which is an indicator for process selectivity and excess final energy use, which is an indicator for the efficiency of energy use of a process. For the majority of processes the excess final energy contribution is the largest.

Considering those processes for which a Best Available Technology is known, the yearly energy saving potential in Western Europe ranges from 10 to 50% for small and large energy consumers respectively.

For the processes in the refinery industry, the analysis is focussed on the energy use of the various processes. The heat effects resulting from the chemical reactions could not be estimated with reasonable accuracy. Total energy use of the processes analysed in 2000 in Western Europe is estimated at 1555 PJf and 1654 PJp. Total CO2 emissions are estimated at 137 Mt CO2. Atmospheric distillation is identified at the largest energy consumer in the refinery (430 PJf), followed by catalytic cracking and hydrogen production.

This report presents an analysis at an intermediate (meso) level. The processes have been studied as black boxes without analysing the various unit operations (reactors, separation equipment etc.) within the process. Adding up the results for all processes yields results for the industries as a whole (the macro level). Processes with large theoretical energy saving potentials in relative and/or absolute terms have been identified. Among these processes are processes that are well known for their large energy use such as the processes to produce ammonia, chlorine and ethylene, but also less well known processes such as the processes to produce acrylonitrile and hexamethylene diamine. These processes could be selected for more detailed analysis at the micro level. In doing so, actual energy saving potentials could be determined, taking into account not only theoretical, but also practical, economic and thermodynamic considerations. The spreadsheet model can also be extended and improved at the meso and macro level. Various recommendations are given for improvements and extensions such as the inclusion of a more sophisticated model section for the production of electricity and steam and the inclusion of dynamic elements in the model to analyse past and to project future energy demand of the chemical and refinery industry.

 


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