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Title Short-term Solar Power Forecasting
Author Bacher, Peder (Mathematical Statistics, Department of Informatics and Mathematical Modeling, Technical University of Denmark, DTU, DK-2800 Kgs. Lyngby, Denmark)
Supervisor Madsen, Henrik (Mathematical Statistics, Department of Informatics and Mathematical Modeling, Technical University of Denmark, DTU, DK-2800 Kgs. Lyngby, Denmark)
Institution Technical University of Denmark, DTU, DK-2800 Kgs. Lyngby, Denmark
Thesis level Master's thesis
Year 2008
Abstract The share of the global power production coming from solar power is increasing. Forecasts of solar power is a key point for a successful integration of the solar power production into the existing electricity grid. In the present thesis a solar power forecasting method is developed. The overall production of 21 grid-connected photovoltaic (PV) systems with peak power in the range of 1 kWp to 4 kWp is used. The PV systems are located within an area of a few square kilometers. Numerical weather predictions (NWP) of global irradiation from the mesoscale NWP model DMI-Hirlam, is also used as input to the method. A clear sky model only based on solar power observations is developed. It is used to transform the solar power process into a stationary process that resembles the transmittance of the atmosphere. This process is modeled with linear models and the best model both with and without NWPs as input is identi¯ed. Adaptive estimation is found to be a requisite. Therefore the prediction models of the transformed solar power process are fitted using k-step recursive least squares with forgetting. The evaluation focus on solar power forecasts for the purpose of bidding into the electricity market Elspot. The forecasts are issued at 12:00 UTC each day and consist of hour value predictions up to a 36 hour horizon of solar power. These forecasts are evaluated and compared to a persistence reference model. The achieved results clearly indicate an increasing performance for next day horizons (12 to 36 hours), by the model using NWPs as input. Whereas for very short-term predictions (less than 6 hours) the solar power observations are the most important input. Finally ideas for both refinements and extensions to the method are outlined, together with a suggestion for the development of a framework for standardization of solar power forecasting method evaluation.
Series IMM-M.Sc.-2008-13
Fulltext
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Admin Creation date: 2008-02-19    Update date: 2009-11-24    Source: dtu    ID: 211035    Original MXD