The substitution of fossil fueled final energy consumption through electrical appliances and processes (electrification), in combination with an increased share of emission free electricity production, poses a promising deep decarbonization strategy. To reveal the effect of high demand‐side electrification rates on the transmission grid and electricity supply‐side a case‐study analysis for the German market is performed. A reference scenario with low demand‐side electrification and low grid congestion is compared to high demand‐side electrification scenarios with two different shares of renewable electricity production of total electrical load: “Elec61” and “Elec75.” The analysis shows that an increase of the electrical load from ~500 TWh to ~760 TWh leads to heightened stress for the transmission grid and therefore more curtailment in both electrification scenarios. In Elec61, which exhibits the same share of renewable electricity production as the reference scenario, the integration of 19 TWh of flexible power‐to‐heat in district heating networks reduces the market driven curtailment of renewable feed‐in, highlighting the value of flexible electrical loads for the integration of variable renewable energy sources. Although a drastic increase of installed renewable electricity production capacity occurs in Elec61 (+109 GW) and Elec75 (+178 GW) compared to the reference scenario, fossil fueled power plants are still being dispatched frequently in times of high electrical load and low renewable energy feed. In the examined scenarios, deep decarbonization through electrification was not possible because the decrease of the CO2‐coefficient of power generation resulting from an increase in the installed capacity of variable renewable energy sources was insufficient. This article is categorized under: Wind Power > Systems and Infrastructure Energy and Climate > Systems and Infrastructure Energy Systems Analysis > Systems and Infrastructure

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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.

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