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1	Power curves of whole wind farms under real operating conditions Raabe, Armin, Wagner, Robert, Zimmer, Janek 03 November 2017 (has links) The time-variable production of wind energy must be included into the time-variable energy consumption schemes. This interactive process depends on a precise prediction of weather conditions, particularly of the wind speed (u), and knowledge of the behavior of the consumers. Parallel to the wind speed prediction the wind energy production depends on the technical parameter of the wind turbines, e.g. characterized by a power curve . As we show here, the power curve of a wind farm, consisting of a number of wind turbines, and an individual power curve of a single wind turbine are different. To systematize the relation between wind speed and energy production the power curve is here approximated using an analytic function. This function fits in our case the predicted wind speed with the predicted or actual energy production of a wind farm. Using this function the behavior of wind farms under real operation conditions are shown. The potential of these wind farm power curves are discussed. These curves are used for the power prediction in a power forecast system based on a neural network. The neural network uses the analytic function to systematize the energy output of the wind farms under different wind field conditions. These analytic power curves are helpful tools to characterize the behavior of a wind farm in a good agreement with the measured power output. Additionally, the analysis of some wind parks shows great differences in the expected power output, depending on the wind direction, the position of each wind turbine and the location of the wind farms in their surroundings. / Die zeitlich variable Produktion von Windenergie muss in das zeitlich variable Energienutzungsverhalten integriert werden. Dieser Wechselwirkungsprozess schließt eine präzise Wettervorhersage, speziell der Windgeschwindigkeit, und die Kenntnis des Verhaltens der Konsumenten ein. Neben der Windfeldvorhersage hängt die Windenergieproduktion auch von den technischen Parametern der Windenergieanlagen ab, die durch eine Leistungskurve p(u) charakterisiert werden kann. Hier wird gezeigt, dass sich die Leistungsabgabe ganzer Windparks von denen einzelner Anlagen stark unterscheidet. Um diesen Zusammenhang zwischen Windgeschwindigkeit und Energieproduktion zu systematisieren, werden hier die Leistungskurven durch eine analytische Funktion approximiert. Diese Funktion stellt in unserem Fall einen Zusammenhang zwischen der prognostizierten Windgeschwindigkeit und der prognostizierten bzw. tatsächlich eingetretenen Energieproduktion her. Mit dieser Funktion wird das Verhalten von Windparks unter realen Betriebsbedingungen gezeigt. Zusätzlich wird das Potenzial der Windpark-Leistungskurven diskutiert. Diese Kurven werden für die Leistungsvorhersage in einem Energieprognosesystem auf Basis eines neuronalen Netzes verwendet. Das neuronale Netz nutzt die analytische Funktion, um den Energieertrag der Windparks unter verschiedenen Windfeldbedingungen zu systematisieren. Die Analyse einiger Windparks zeigt große Unterschiede zwischen der erwarteten Ausgangsleistung in Abhängigkeit von der Windrichtung, von der Position jeder Windkraftanlage und der Lage des Windparks in seiner Umgebung. info:eu-repo/classification/ddc/551 ddc:551
2	Assessing the potential of fuel saving and emissions reduction of the bus rapid transit system in Curitiba, Brazil Dreier, Dennis January 2015 (has links) The transport sector contributes significantly to global energy use and emissions due to its traditional dependency on fossil fuels. Climate change, security of energy supply and increasing mobility demand is mobilising governments around the challenges of sustainable transport. Immediate opportunities to reduce emissions exist through the adoption of new bus technologies, e.g. advanced powertrains. This thesis analysed energy use and carbon dioxide (CO2) emissions of conventional, hybrid-electric, and plug-in hybrid-electric city buses including two-axle, articulated, and biarticulated chassis types (A total of 6 bus types) for the operation phase (Tank-to-Wheel) in Curitiba, Brazil. The systems analysis tool – Advanced Vehicle Simulator (ADVISOR) and a carbon balance method were applied. Seven bus routes and six operation times for each (i.e. 42 driving cycles) are considered based on real-world data. The results show that hybrid-electric and plug-in hybrid-electric two-axle city buses consume 30% and 58% less energy per distance (MJ/km) compared to a conventional two-axle city bus (i.e. 17.46 MJ/km). Additionally, the energy use per passenger-distance (MJ/pkm) of a conventional biarticulated city bus amounts to 0.22 MJ/pkm, which is 41% and 24% lower compared to conventional and hybrid-electric two-axle city buses, respectively. This is mainly due to the former’s large passenger carrying capacity. Large passenger carrying capacities can reduce energy use (MJ/pkm) if the occupancy rate of the city bus is sufficient high. Bus routes with fewer stops decrease energy use by 10-26% depending on the city bus, because of reductions in losses from acceleration and braking. The CO2 emissions are linearly proportional to the estimated energy use following from the carbon balance method, e.g. CO2 emissions for a conventional two-axle city bus amount to 1299 g/km. Further results show that energy use of city bus operation depends on the operation time due to different traffic conditions and driving cycle characteristics. An additional analysis shows that energy use estimations can vary strongly between considered driving cycles from real-world data. The study concludes that advanced powertrains with electric drive capabilities, large passenger carrying capacities and bus routes with a fewer number of bus stops are beneficial in terms of reducing energy use and CO2 emissions of city bus operation in Curitiba. advanced powertrain Advanced Vehicle Simulator ADVISOR Brazil BRT bus rapid transit carbon dioxide CO2 city bus Curitiba driving cycle emissions energy consumption energy efficiency energy use fuel economy hybrid propulsion hybrid-electric parallel hybrid passenger carrying capacity plug-in hybrid-electric Tank-to-Wheel analysis vehicle simulation Analyse Brasilien Emissionen Energieeffizienz Energienutzung Energieverbrauch Fahrzeugsimulation Fahrzeugwirkungsgrad Fahrzyklus Fortschrittlicher Antriebsstrang Hybridantrieb Hybridelektrofahrzeug Kohlenstoffdioxid Kraftstoffverbrauch Passagiertransportkapazität Schnellbussystem Stadtbus Steckdosen-Hybrid Vollhybrid analys bränsleförbrukning drivlina energianvändning energieffektivit energiförbrukning fordonssimulering hybriddrift koldioxidutsläpp körcykel laddhybrid passagerarkapacitet stadsbuss strombuss Energy Engineering Energiteknik Energy Systems Energisystem Vehicle Engineering Farkostteknik

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Power curves of whole wind farms under real operating conditions

Assessing the potential of fuel saving and emissions reduction of the bus rapid transit system in Curitiba, Brazil