Optimal Supply with Energy Services

The supply of residential buildings with energy services (e.g. warm and bright rooms, hot water and meals, mobility, electric-specific services) is currently characterised by the use of exhaustible non-indigenous energy carriers and by high losses due to low efficiency of conversion technologies, poor thermal quality of buildings and a centralised supply system with inherent distribution losses. Moreo-ver, the system has a high environmental impact and, furthermore, a considerable amount of energy - "embedded" energy - is spent for the production of conversion technologies. These features especially apply to industrialised countries. The basic idea of this project is that this structure could be changed towards a sustainable system if technologies were selected in an optimal way from society`s point-of-view. Hence, the core questions to be answered are: How would an optimal supply of energy services for residential buildings from society`s point-of-view look? Which technologies are of priority for an op-timal supply? How can optimal supply be brought about in a dynamic framework? In this context the major optimisation objective is to minimise societal costs, that is to say the sum of monetary and external costs, by modelling consumers` decision-making process and including external costs. To get an appraisal of the sensitivity of this solution other objectives are addressed, as there are to minimise pure industrial costs (monetary costs), to minimise greenhouse gas emissions and to minimise embedded energy respectively. The following methodology is applied analysing the existing building stock and new buildings sepa-rately: (1) The residential building types investigated are defined and (2) final energy demand for the three main energy services, namely space heating, water heating and electric specific uses, is modelled. (3) Technologies considered in this project are specified providing an extensive database of parame-ters, such as efficiencies, costs, learning curves, etc. Three basic groups of technologies are identified: (a) supply-side technologies (b) building technologies and (c) demand-side technologies; (4) Consumers` decision making process is modelled according to the different objectives. (5) The decision making processes are integrated in a dynamic framework analysing various periods of time (e.g. 2000 to 2030) and are applied to Austria as a case study. (6) Finally, the results of the major objective and the alternative approaches are compared deriving requirements for necessary technology progress, R&D needs, and efficient energy strategies.

Big potentials for reductions of greenhouse gas (GHG) emissions and energy consumption could be realised by improving the thermal quality of the residential building stock and by introducing renewable energy technologies in this sector. From societys point-of-view the following objectives can be pursued for the purpose of choosing technologies resp. measures to tap this potential: minimise societal costs (=sum of monetary and external costs) minimise greenhouse gas emissions (life-cycle perspective, considering investment and operation) minimise energy consumption (life-cycle perspective) A simulation tool was developed within this project which is applied to investigate the influence of the above mentioned objectives on technology choice, level of greenhouse gas emissions and energy consumption for space heating and domestic hot water supply of Austrias residential building stock until the year 2020. The results achieved when applying these optimisation objectives are contrasted with application of the objective "minimise monetary costs" which represents the decision process of a consumer deciding rationally in a narrow economic sense. Essential frame work conditions like development of energy prices or renovation rates are defined in a "baseline- scenario". Given the assumptions of this baseline-scenario substantial reductions of greenhouse gas emissions result when applying any of the optimisation objectives, even in the case "minimise monetary costs" (33% reduction, comparison 2020 - 2002, only for existing buildings). Further reductions are observable in the cases "minimise societal costs" (40%) and "minimise life-cycle greenhouse gas emissions" (49%), but at rather different costs. An additional saved ton of greenhouse gases (given greenhouse gas emissions of "minimise monetary costs" as reference) costs about 4 times less in the case "minimise social costs" compared with "minimise life-cycle greenhouse gas emissions". Hence in the case of "minimise life-cycle greenhouse gas emissions" relatively expensive technologies like solar combi systems (combination of solar space and water heating) are deployed. In every simulation run given the price assumptions of the baseline-scenario there is a massive shift away from oil as an energy carrier for heating, apart from "minimise monetary costs" there is also a shift away from natural gas. This indicates that current energy price relations (with the assumption of a moderately rising trend) would be incentive enough for this kind of fuel shift assuming pure economic calculation. The relative importance of district heating and biomass energy carriers grows. The simulation results support the view that sensibly chosen schemes for investment subsidies may direct residential energy supply structure towards societally optimal paths. However, there exists a trade-off between efficiency (ratio of public money spent and saved greenhouse gas emissions, compared to the case without subidy) and the effectiveness (total amount of greenhouse gas emissions saved due to the subsidy) of different subsidy schemes which has to be addressed in the process of political decision making.