• Energy Research

The European Union and the Austrian government have set ambitious plans to expand renewable energy sources and lower carbon dioxide emissions. However, the expansion of volatile renewable energy sources may affect today’s energy system. To investigate future challenges in Austria’s energy system, a suitable simulation methodology, temporal and spatially resolved generation and consumption data and energy grid depiction, is necessary. In this paper, we introduce a flexible multi-energy simulation framework with optimization capabilities that can be applied to a broad range of use cases. Furthermore, it is shown how a spatially and temporally resolved multi-energy system model can be set up on a national scale. To consider actual infrastructure properties, a detailed energy grid depiction is considered. Three scenarios assess the potential future energy system of Austria, focusing on the power grid, based on the government’s renewable energy sources expansion targets in the year 2030. Results show that the overwhelming majority of line overloads accrue in Austria’s power distribution grid. Furthermore, the mode of operation of flexible consumer and generation also affects the number of line overloads as well.

Iron & Steel, Pulp & Paper, Non-Metallic Minerals and Chemical & Petrochemical are the most energy intensive subsectors, even though they utilise only a limited range of production processes compared to other sectors like Machinery or Food & Beverages. To support future efforts for decarbonising the European industry, this study aims to develop a methodology to correctly and dynamically depict all relevant production processes of the mentioned subsectors and to generate synthetic load profiles (LP)1 based upon their consumption and generation behaviour. In a first step, the energy intensive subsectors and their main production processes are identified. A standardised research approach is used to correctly depict their characteristics e.g. runtime, energy consumption and generation, unit sizes etc. Next, a methodology for modelling the timely behaviour of these production processes and for generating synthetic LPs is developed. This method is based upon the bottom-up approach of discrete-event simulation combined with stochastics. The developed methodology is then implemented into the simulation software Ganymed. Finally, the results of this methodology are validated via a case study, modelling the primary steel production route of an Austrian steel mill. In overall, the synthetic electricity LP shows good approximations to the measured one with a mean absolute percentage error of 6.08% for the simulated five days in total. However, a stronger deviation of the generated LP compared to the measured counterpart can be noted at the last two days. This deviation results from a reduction of the capacity during the real life production. This, however, can be taken into account in the synthetic generation given a more extensive data basis. Consequently, Ganymed can be deemed as a suitable software for generating energy consumption and generation behaviour of processes and production chains of energy intensive industries.

In developed countries like Austria the renewable energy potential might outpace the demand. This requires primary energy efficiency measures as well as an energy system design that enables the integration of variable renewable energy sources. Municipal energy systems, which supply customers with heat and electricity, will play an important role in this task. The cumulative exergy consumption methodology considers resource consumption from the raw material to the final product. It includes the exergetic expenses for imported energy as well as for building the energy infrastructure. In this paper, we determine the exergy optimal energy system design of an exemplary municipal energy system by using cumulative exergy consumption minimisation. The results of a case study show that well a linked electricity and heat system using heat pumps, combined heat power plants and battery and thermal storages is necessary. This enables an efficient supply and also provides the necessary flexibilities for integrating variable renewable energy sources.

The industry is responsible for 24% of anthropogenic emissions and a quarter of total energy consumption worldwide. Accelerating the action plan for climate neutrality for the industry, particularly the energy-intensive industrial subsectors, which are responsible for about 70% of the sector's emissions and energy consumption, is crucial to achieving the climate change goals. Iron and steel, pulp and paper, nonmetallic minerals emphasizing cement and nonferrous metals focusing on aluminum are the four energy-intensive industrial subsectors investigated in this study. We evaluate the benefits and obstacles of various mitigation methods for each subsector over two time horizons: short/medium-term emission reductions and long-term emission reductions. Actions that have already been implemented in some industrial sites and do not require extensive infrastructural upgrades are generally considered in the short/medium term. This group covers boosting energy efficiency by retrofitting plants and adopting the best available or best practice technologies in existing process stages, as well as substituting fossil fuels as energy sources with bioenergy, hydrogen, or electricity (low-emission electricity). This strategy can reduce emissions in the shortest possible timeframe; nevertheless, the reduction is insufficient, and additional efforts are required to transition the industry to a low-carbon economy by 2050. These further efforts are viewed as long-term reductions that broadly address mitigation alternatives connected to process emissions, which are an inherent part of the production processes of industrial subsectors across a more extended period. The frontline technologies studied in this category are fossil fuel feedstock change to non-fossil gases such as hydrogen, carbon capture usage and storage, a higher degree of electrification and increased use of secondary raw material. By evaluating the conditions for each subsector, this study also analyses the industrial landscape along the industrial value chain, showing that all of these four technology groups need to be implemented in a sector-specific approach to close the ambitious net-zero emissions gaps. In this essay, Austrian energy-intensive industrial subsectors are assessed as case studies using a comprehensive approach that includes influencing factors such as the subsector's current energy and emissions intensity, energy infrastructure, future national and international policies, and related decarbonization techniques. Transitioning from fossil fuels to emission-free fuels as raw materials (in the iron and steel subsector) and energy sources, as well as circular economy paths, have more potent effects on decarbonizing the Austrian industry. When these strategies are integrated with CO₂ capture solutions for the cement industry and energy efficiency improvements for relevant subsectors, Austrian industrial emissions can be reduced by more than 65% compared to the current level.

Efficiency measures and the integration of renewable energy sources are key to achieving a sustainable society. The cumulative exergy consumption describes the resource consumption of a product from the raw material to the final utilisation. It includes the exergy expenses for energy infrastructure as well as the imported energy. Since consumers and renewable potentials are usually in different locations, grid restrictions and energy flows have a significant impact on the optimal energy system design. In this paper we will use cumulative exergy minimisation together with load flow calculations to determine the optimal system design of a multi-cell municipal energy system. Two different load flow representations are compared. The network flow model uses transmission efficiencies for heat, gas and electricity flows. The power flow representation uses a linear DC approximated load flow for electricity flows and a MILP (mixed integer linear programming) representation for heat and gas flows to account for the nonlinear pressure loss relation. Although both representations provide comparable overall results, the installed capacities in the individual cells differ significantly. The differences are greatest in well meshed cells, while they are small in stub lines.

To achieve climate goals, it is necessary to decarbonise the transport sector, which requires an immediate changeover to alternative power sources (e.g., battery powered vehicles). This change will lead to an increase in the demand for electrical energy, which will cause additional stress on power grids. It is therefore necessary to evaluate energy and power requirements of a future society using e-mobility. Therefore, we present a new approach to investigate the influence of increasing e-mobility on a distribution grid level. This includes the development of a power grid model based on a cellular approach, reducing computation efforts, and allowing time and spatially resolved grid stress analysis based on different load and renewable energy source scenarios. The results show that by using the simplified grid model at least seven times, more scenarios can be calculated in the same time. In addition, we demonstrate the capability of this novel approach by analysing the influence of different penetrations of e-mobility on the grid load using a case study, which is calculated using synthetic charging load profiles based on a real-life mobility data. The results from this case study show an increase on line utilisations with increasing e-mobility and the influence of producers at the same connection point as e-mobility.

Abstract Thermal energy storage (TES) can play a key role in increasing primary energy efficiency in the industrial sector. Differences in location-specific conditions lead to differences in TES requirements across companies and to a lack of techno-economic knowhow regarding standardized implementation. This study provides a techno-economic overview of potential TES technologies (sensible, latent, thermochemical, and sorption) based on key performance indicators (KPI) and performs a qualitative pre-selection of the TES to be used in specific industrial branches at specific temperature levels. The outcome is a TES application matrix for industrial branches based on the quantified energetic and exergetic heat demand per temperature level and branch. This matrix is expected to facilitate and support the selection of future TES projects. The study demonstrates its methodology of estimating the energetic and exergetic heat demand of a country by applying it to Austria. In this case, the estimated energetic industrial heat demand is about 88 TWh/year, and the exergetic industrial heat demand is about 50 TWh/year. In the application matrix, 2,470 variants of industrial energetic heat demand and potential TES applications are evaluated. The results show that there is only a 6% match between a TES priority field of application and the fields with the greatest energetic heat demand. As the costs of a TES system influence its industrial use, an economic top–down method of determining the maximum costs (and thus economic viability) of a TES system is presented. The generic approach is demonstrated by conducting a case study of a cement plant. The acceptable storage costs are derived by determining the energy and cost savings relative to a conventional gas-driven energy supply system. Depending on the size of the TES, the acceptable costs are found to vary between 1.4 and 14.4 €/kWh for a capacity of 500 MWh and 1 MWh, respectively. A sensitivity analysis is also conducted to show how gas and CO2 emission allowance prices affect the acceptability of storage costs. The study also discusses the main considerations and factors in efficient TES selection and successful system integration. Finally, the development and innovation required to increase industrial use are outlined. The study's economic analysis of TES integration in a cement plant shows that TES implementation is not feasible under the present conditions unless appropriate measures and incentives are applied.