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Integrating variable and non-dispatchable renewable power generation into existing power systems will have consequences for their operation and future expansion. These impacts will depend on two factors: (1) the variability of the total renewable power generation on different time scales and (2) the possibilities of accurately forecasting these fluctuations. In this paper, previous research on variability assessment and forecasting of solar, wind, wave and tidal energy resources is reviewed. The aim is to summarize the state of knowledge in each area and to compare the approaches used for the respective resources. For temporal variability, methods and models used for assessing the variability are surveyed, as well as what is known about the variability at individual sites and for larger aggregates of sites. For forecasting, an overview of forecasting methods for the different resources is made, and selected forecasting methods are compared over different time horizons. An important finding is that it is hard to draw strong conclusions from the existing studies due to differences in approaches and presentation of results. There is a need for further, more coherent studies that analyze the variability for the different resources in comparable ways, using data with the same resolution, and for studies that evaluate the smoothing effect and complementarity of combinations of several renewable energy resources. For forecasting, future research should suggest ways to evaluate forecasts from different renewable energy sources in easily comparable ways, using data from the same locations or regions, with the same temporal and spatial resolution, and with comparable metrics for the forecasting errors. [ABSTRACT FROM AUTHOR]

Abstract: Successful technological innovation frameworks are based on synergistic packages of technology-push and demand-pull measures. As the massive deployment of premature renewable energy technologies risks becoming very expensive, the debate on the optimal trajectory of renewable technologies should explicitly consider the balance between deployment incentives and R&D efforts. This paper explores this balance regarding wind and PV technology support in Europe. Based on rather conservative estimates, we calculate future deployment costs and compare these figures to the current public investments in PV and wind R&D. We find that, today, for each Euro spent on R&D to develop future technologies, 35 to 41 Euros are spent on the deployment of existing technologies. Furthermore, private PV and wind technology companies tend to underinvest in R&D for various reasons. In an alternative scenario, we assess the optimal R&D efforts for the PV and wind sectors based on a 7% R&D-to-sales benchmark that is typical for engineering sectors. If public R&D efforts would increase according to this benchmark, and hence compensate for the private underinvestments in R&D, pull/push ratios between 6 and 8 could be achieved. This leads us to conclude that the current balance between deployment and R&D is far from optimal. [Copyright &y& Elsevier]

Abstract: Turkey is a rich country from the point of variety and potential of renewable energy resources. Hydros, winds, biomass, solar and geothermal are important renewable and environmentally friendly sources for energy in Turkey. Turkey produces large amount of hydropower with a total gross hydropower potential of 433TWh/yr, which is equal to 13.8% of the total hydropower potential of Europe. Technically useable potential is 216TWh/yr and economic potential is 140TWh/yr. The main aim of the present study is to investigate hydropower potential of Turkey and small hydropower plants in Eastern Black Sea Region for sustainable energy development in Turkey. The geography of Turkey especially, Eastern Black Sea Region supports and suitable the development of the small hydro plants to increase the energy generation and utilization of available water sources in Turkey. Besides, the paper deals with hydropower policies to meet ever increasing energy demand for sustainable development of Turkey. [Copyright &y& Elsevier]