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Highlights • Analysis of possible energy savings in the German chemical industry. • Uncertainty analysis of costs and potentials of energy saving measures. • Evaluation of marginal cost curves of energy savings with uncertainties. • Determination of important model parameters using sensitivity analysis. Abstract In 2014, 19.3% of Germany’s industrial final energy consumption could be allocated to the chemical industry. Energy efficiency measures with focus on the chemical industry could thus contribute to reaching the German goal of reducing greenhouse gas emissions. To achieve this goal, energy planners and industries alike require an overview of the existing energy efficiency measures, their technical potential as well as the costs for realizing this potential. Energy efficiency opportunities are commonly presented in marginal cost curves, which rank these measures according to specific implementation costs. Existing analyses, however, do not take uncertainties in costs and potentials sufficiently into account. The aim of this paper is to create a marginal cost curve of energy efficiency measures for the chemical industry in Germany, while quantifying the uncertainties of the results and identifying the most influential input parameters. The identification of energy efficiency measures and the quantification of the associated technical potentials and costs were identified based on literature data and own assessments. Based on these findings a cost curve was created for the current technical potential. This potential was found to be 24.4 PJ per year, of which 23 PJ had negative lifetime costs. To investigate the uncertainties of these results, Monte Carlo simulations were performed to quantify the standard deviations of the implementation potential and costs. Furthermore, a sensitivity analysis, based on Morris Screening and linear regression, was conducted in order to identify the most influential model input parameters. With the applied approach, it was shown that uncertainties have a non-negligible impact on the final energy saving potential and costs, as well as the shape of marginal cost curves. The standard deviation of the energy saving potential was found to be 3.1 PJ. Furthermore, it is possible to systematically prioritise efforts in refining data. [ABSTRACT FROM AUTHOR]

Excess heat is present in many sectors, and its utilization could reduce the primary energy use and emission of greenhouse gases. This work presents a geographical mapping of excess heat, in which excess heat from the industry and utility sector was distributed to specific geographical locations in Denmark. Based on this mapping, a systematic approach for identifying cases for the utilization of excess heat is proposed, considering the production of district heat and process heat, as well as power generation. The technical and economic feasibility of this approach was evaluated for six cases. Special focus was placed on the challenges for the connection of excess heat sources to heat users. To account for uncertainties in the model input, different methods were applied to determine the uncertainty of the results and the most important model parameters. The results show how the spatial mapping of excess heat sources can be used to identify their utilization potentials. The identified case studies show that it can be economically feasible to connect the heat sources to the public energy network or to use the heat to generate electricity. The uncertainty analysis suggests that the results are indicative and are particularly useful for a fast evaluation, comparison and prioritization of possible matches. The excess heat temperature and obtainable energy price were identified as the most important input parameters. [ABSTRACT FROM AUTHOR]