Marianne Zeyringer

Solar buildings in Austria: Methodology to assess the potential for optimal PV deployment

A high rate of integration of distributed photovoltaic systems (PV) may cause problems in the distribution grid. We propose a methodology to spatially and temporally analyze the potential reverse load in the distribution grid of Austria. The goal lies in determining the maximum generation of PV with no investments into grid enforcements. First, we use measured load profiles for households and simulate stochastic load profiles for commercial consumers. We combine the generated load profiles with data on PV output to determine the net demand load profiles at 1 km2 grid. Thirdly, we study the effects of a large scale implementation of rooftop PV on the energy system using the JRC EU TIMES model. We find that (excluding night hours) on average in 9% of the hours supply exceeds demand, differing between 0% and 60% depending on the grid cell. When only including household load profiles, surplus production increases to 23%. This suggests to giving priority to decentralized PV development in areas with a higher share of commercial consumers. Lastly, we show that a large scale deployment of distributed PV leads to reduced imported electricity.

The impact of location on competitiveness of wind and PV electricity generation - Case study for Austria

The generation potential of renewable energy sources and their time profile of production depends on geographic characteristics. Furthermore, the integration of renewable energy technologies into the energy system is constrained by existing distribution infrastructure. The paper does a preliminary assessment on how the availability of spatially and temporally highly resolved data on resource potentials may affect the projections on the development of wind and photovoltaic electricity generation in Austria, using the technology bottom-up JRC EU TIMES optimization model. In particular, we assess the differences in costs and CO2 emissions between a spatially disaggregated and an aggregated approach. Results show that disaggregating RES locations significantly affects results especially for wind leading to higher electricity generation from wind and reduced electricity trade with other countries.

A spatially and temporally highly resolved analysis of wind power potentials in Austria

The Austrian energy action plan 2010 aims at increasing annual wind power production by 3 TWh until 2020. A recent study assessed optimal locations for wind power plants based on the calculation of production costs derived from wind speeds modeled in a spatially explicit way for Austria. However, wind power production, as any other intermittent renewable power source, can be highly variable due the stochastic nature of wind. This may incur additional costs for regulating power or storage devices. Selecting wind power production sites by minimizing the variability of joint power output may be one way to manage intermittency. We have generated synthetic time series of wind power production using data from a wind atlas and meteorological stations. We used the time series in an optimization model to analyze how variability in the output of newly added wind turbines can be decreased by diversifying the sites of wind farms. Results indicate that hourly variability as well as seasonal variability can be reduced by diversification of turbine sites, however, there is a trade-off. Model results indicate that diversification will reduce rents of wind turbine developers by increasing costs although all assessed sites are profitable when considering current feed-in tariffs. This implies that regulators could increase the usability of wind power plants by taking into account diversification of locations without increasing costs for consumers.1