20% by 2020? Economy-wide impacts of energy efficiency improvement in Germany

The paper presents results of the implementation of an efficiency strategy in Germany until 2020 which is focused on cost-effective measures. The efficiency measures are calculated in bottom-up models and translated into a top-down macro-economic model. The comparison to a business as usual simulation shows some economy-wide rebound effects of about 17% of the overall energy savings. The analysis is limited to 2020. Given that an efficiency strategy is a long-term strategy, this puts the results on the rather conservative side. The results clearly show that improved energy efficiency results in a variety of positive effects on the economy and the environment. These range from reduced greenhouse gas emissions to improved competitiveness of firms and budget savings for consumers to economy wide impacts like additional employment and economic growth. Even the consideration of rebound effects did not change this picture significantly. Thus, exploiting the huge potential stemming from cost-effective efficiency measures should have high priority for the design of energy and climate policies.energy efficiency, bottom up scenario analysis, climate policy

Integration Erneuerbarer Energieträger in industrielle Hochtemperaturprozesse: Technische Grenzen des Energieträgerwechsels

Industrielle Aktivität im Hochtemperaturbereich stellt besondere Anforderungen an die verwendeten Energieträger. Zu den üblichen wirtschaftlichen Überlegungen der Energieversorgung kommen technische Aspekte, die aufgrund der Heterogenität der in der Industrie verwendeten Verfahren nicht aggregiert betrachtet werden können. Für die Modellierung der Energienachfrage beispielsweise in Bottom-up Modellen ist jedoch auch bei hohem Detailgrad eine gewisse Abstraktion notwendig. Oft verbleiben Energienachfragemodelle dabei auf der Subsektorebene, wodurch wirtschaftliche Zusammenhänge ausreichend dargestellt werden können, technische Aspekte der Verfahren aber verwaschen werden. Eine mögliche detailliertere Untersuchungsebene stellen Prozesse, charakterisiert durch vergleichbare technische Einrichtungen und hergestellte Produkte, dar. In diesem Artikel zeigen wir eine Methode auf, durch die technische Details auf Prozessebene mit der wirtschaftlichen Betrachtung auf Subsektorebene verbunden werden können. Die modellierten Effekte betreffen den Einsatz von niederkalorischen Brennstoffen (Müll, Biomassen) als Ersatz für fossile Energieträger. Ergebnisse eines Beispielszenarios zeigen geringe, aber nicht zu vernachlässigende Effekte auf den Brennstoffmix (Verschiebung von 3% der untersuchten Energiemenge)

The effect of low-carbon processes on industrial excess heat potentials for district heating in the EU: a GIS-based analysis

The two datasets are supplement to the publication Manz, Pia; Fleiter, Tobias; Eichhammer, Wolfang: "The effect of low-carbon processes on industrial excess heat potentials for district heating in the EU: a GIS-based analysis" (to be published). Excess heat from industrial processes can be utilized in district heating networks, thereby reducing the primary energy demand and possibly CO2 emissions for district heating generation. Many studies found a substantial potential of industrial excess heat; however, they did not systematically consider the potential future changes in the energy system that will affect the potential excess heat utilization. Industrial production will transform to low-carbon processes and district heating needs to be generated without fossil fuels. Here, we quantify industrial excess heat by spatial matching for the EU-27, considering the impact of the transformation to a climate-neutral energy system. In a first step, excess heat potentials from energy-intensive industries are identified as point sources, taking into account process changes. In a subsequent step, the excess heat potentials are spatially matched to district heating areas with a GIS-based approach. The results show, that available excess heat will reduce significantly due to industry transformation. At the same time, the utilization potential could be increased by lower district heating system temperatures and by an expansion of district heating areas, resulting in 3 - 36 TWh/a. Locally, there is a significant contribution of industrial excess heat in the future, even though the major share will need to be supplied by renewables.Reiner-Lemoine-StiftungFraunhofer Cluster of Excellence "Integrated Energy Systems" (CINES)Open in Microsoft Excel.Data of excess heat sources are georeferenced with coordinates, open in GIS (WGS 84 (4326)

Inter-fuel substitution in European industry : A random utility approach on industrial heat demand

As the majority of industrial emissions stems from heat generation, the choice of fuel is, next to energy efficiency, one of the tools to influence climate impact (and security of supply) in industrial energy use. At the same time, the choice of fuel is not only a matter of price but of the furnace, it is used in. Top-down models often struggle to include technological explicitness, which is especially important to represent the heterogeneous structure of industrial energy demand. In this paper, an approach to apply a discrete choice model to industrial high temperature energy demand is presented. The model's parameters are estimated based on observed fuel choices. The model exhibits an average coefficient of determination of 0.45 when compared to a constant fuel use from 2002 to 2013 in major countries of the European Union. Results suggest that energy carriers are perceived very differently by industrial consumers

Inter-fuel substitution in European industry : A random utility approach on industrial heat demand

As the majority of industrial emissions stems from heat generation, the choice of fuel is, next to energy efficiency, one of the tools to influence climate impact (and security of supply) in industrial energy use. At the same time, the choice of fuel is not only a matter of price but of the furnace, it is used in. Top-down models often struggle to include technological explicitness, which is especially important to represent the heterogeneous structure of industrial energy demand. In this paper, an approach to apply a discrete choice model to industrial high temperature energy demand is presented. The model's parameters are estimated based on observed fuel choices. The model exhibits an average coefficient of determination of 0.45 when compared to a constant fuel use from 2002 to 2013 in major countries of the European Union. Results suggest that energy carriers are perceived very differently by industrial consumers

Developing a georeferenced database of energy-intensive industry plants for estimation of excess heat potentials

Industrial excess heat may be one of the pillars needed to transform the energy system. Integrating excess heat in district heating networks can reduce the primary energy demand of the heating sector. Thus, industrial sites need to be analysed in high spatial resolution with regard to heating demand and excess heat potentials. This paper presents a methodology to estimate site-specific excess heat potentials for industrial plants in Europe. Different data sources are matched and analysed to collect information about CO2 emissions, subsector (NACE and ETS activity), process and production capacity per site in the EU28, Switzerland and Norway. From this dataset of energy-intensive industries (steel, paper, cement and glass), the fuel demand is calculated for each site and process. Two different approaches are used to calculate the fuel demand: first, based on the CO2 emissions, and second, the production capacity in tonnes per year of each site. These two approaches are compared and their accuracy is analysed. In this paper, the excess heat potentials for the most important industrial sectors in Europe are estimated based on process-specific fuel demand for different temperature levels

A bottom-up estimation of the heating and cooling demand in European industry

Energy balances are usually aggregated at the level of subsector and energy carrier. While heating and cooling accounts for half the energy demand of the European Union’s 28 member states plus Norway, Switzerland and Iceland (EU28 + 3), currently, there are no end-use balances that match Eurostat’s energy balance for the industrial sector. Here, we present a methodology to disaggregate Eurostat’s energy balance for the industrial sector. Doing so, we add the dimensions of temperature level and end-use. The results show that, although a similar distribution of energy use by temperature level can be observed, there are considerable differences among individual countries. These differences are mainly caused by the countries’ heterogeneous economic structures, highlighting that approaches on a process level yield more differentiated results than those based on subsectors only. We calculate the final heating demand of the EU28 + 3 for industrial processes in 2012 to be 1035, 706 and 228 TWh at the respective temperature levels > 500 °C (e.g. iron and steel production), 100–500 °C (e.g. steam use in chemical industry) and < 100 °C (e.g. food industry); 346 TWh is needed for space heating. In addition, 86 TWh is calculated for the industrial process cooling demand for electricity in EU28 + 3. We estimate additional 12 TWh of electricity demand for industrial space cooling. The results presented here have contributed to policy discussions in the EU (European Commision 2016), and we expect the additional level of detail to be relevant when designing policies regarding fuel dependency, fuel switching and specific technologies (e.g. low-temperature heat applications)