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Item-typ:Veröffentlichung, Spatio-temporal characterization of long-term solar resource using spatial functional data analysis: Understanding the variability and complementarity of global horizontal irradiance in EcuadorUnderstanding the spatio-temporal variability of the solar resource is crucial to effectively support solar power utilization. Unfortunately, long-term and high-resolved measurements of solar irradiance are generally scarce, challenging the characterization for larger areas. In this paper, we propose a methodology to characterize the spatio-temporal variability of global horizontal irradiance (GHI) at a regional scale using long-term satellite-derived data. Spatial functional data analysis (sFDA) is used to identify areas with similar intra-annual variability patterns. The methodology is applied to a 21-year period data on Ecuador retrieved from the National Solar Radiation Database. Being the first time that sFDA is used for this purpose, the results indicate that it provides an appropriate basis for the interannual variability and complementarity analyses. In Ecuador's mainland, twenty-two subregions with four seasonal patterns are identified. The highest GHI potential (5.4 kWhm−2d−1) with the lowest variability (3.4%) is found in the Inter-Andean valleys. Further, seasonal complementarities between the coast and western Andes are identified. In Galapagos, high values are found over all islands (≥4.8 kWhm−2d−1), characterized by three subregions with one seasonal pattern. Our findings provide the first comprehensive spatio-temporal characterization of GHI in Ecuador, which aims at supporting a sustainable energy transition in the country.Wissenschaftlicher ArtikelBand:18963 166 - Some of the metrics are blocked by yourconsent settings
Item-typ:Veröffentlichung, IR thermographic flow visualization for the quantification of boundary layer flow disturbances due to the leading edge condition(Elsevier Science, 2019-08); ; ; ; The aerodynamic performance of wind turbine rotor blades is influenced by the leading edge condition. Contamination and erosion cause increased surface roughness, unevenness or defects, which affect the boundary layer flow and, thus, reduce lift and increase drag. Current approaches used to determine the disturbed boundary layer flow are based on invasive flow probes with limited spatial resolution; therefore, a non-invasive, camera-based measurement of the boundary layer flow disturbances on wind turbines in operation is proposed using thermographic flow visualization. The actual and the undisturbed laminar-turbulent transition positions are determined in the thermographic images and a subsequent assignment to the rotor blade geometry obtains chord-based information. The normalized difference of both transition positions can be used as a metric to describe the extent of the disturbed boundary layer flow. The approach is demonstrated on a multi-MW horizontal axis wind turbine with a laminar flow reduction of up to 90.4 %. Furthermore, the measurement results allow the estimation of the annual energy production loss due to the leading edge condition, which enhances the industrial standard of simply comparing clean and tripped aerodynamic polars. For the investigated wind turbine, the annual energy production loss amounts to 4.7 % at 6 m/s average wind speed.Wissenschaftlicher ArtikelBand:13870 94 - Some of the metrics are blocked by yourconsent settings
Item-typ:Veröffentlichung, Geographical comparison between wind power, solar power and demand for the German regions and data filling concepts(Elsevier Science, 2018-10); ; ; ; The rising penetration of renewable energies became an important issue in the German electricity sector within the past years. In order to plan the required infrastructure for the energy distribution, a detailed knowledge about the complete geographical and temporal power generation compared to the demand is crucial. However, the available data for the renewable power generation in Germany is insufficient due to the complexity of the energy system. For this reason, a comparison between the renewable power generation and the electricity demand is presented for 95 German zip code regions based on real input data with a sample time of 15 min from renewable energy generators. For enhancing the incomplete data, different model-based data filling methods using the data of neighboured regions or additional meteorological data are introduced and compared. As a result, a number of modelling methods, based either on a heuristic model, a wind speed model or a combination of both, has been investigated, leading to similar correlation coefficients of above 80%. Finally, the obtained data set is applied for an analysis with a high spatiotemporal resolution. For three use cases the resulting optimal flow of the inter-regional power transfers is calculated.Wissenschaftlicher ArtikelBand:12683 101