Physical Approach to Short-Term Wind Power Prediction

By Matthias Lange, U. Focken. 2005

333 citations recorded by the source corpus.

Subfields: Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/8982c2923e2e3f5c7e885cb0fe97a8e93c8315cb

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In Electrical and Electronic Engineering

Citations in the corpus

Assessing the economics of large Energy Storage Plants with an optimisation methodology (2015, background): “The residual error between real data and model results depends on the leadtime considered and on geographical aspects [7,12].”
Wind Integration in Power Systems: Operational Challenges and Possible Solutions (2011, background): “The basic premise in this paper is that the boundaries between unit commitment (UC) functions, on one side, and economic dispatch (ED) of committed units, on the other, are no longer pronounced because of the limited predictability of highly variable wind resources.”
Wind Energy: Forecasting Challenges for Its Operational Management (2013, background): “For an exhaustive review of the state of the art in that field, the reader is referred to Giebel et al. (2011), while a solid introduction to the physical concepts involved can be found in Lange and Focken (2006).”
A new high-dimensional time series approach for wind speed, wind direction and air pressure forecasting (2017, methodology): “Lange and Focken (2006) take the calculated values of a NWP model as input quantities and apply a model to obtain better forecasts.”
Short-term wind power forecasting in Portugal by neural networks and wavelet transform (2011, background): “In the technical literature, several methods to predict wind power have been reported, namely physical [6] and statistical methods [7].”
Markov chain modeling for very-short-term wind power forecasting (2015, background): “The former [3–6] re based on physical considerations to provide estimates of future ind power output starting from meteorological predictions.”
Stochastic Optimization Model to Study the Operational Impacts of High Wind Penetrations in Ireland (2011, background): “It is assumed that the distribution of the wind speed error follows a Gaussian distribution [24].”
Powering Up With Space-Time Wind Forecasting (2010, background): “Predictions of wind speed are ultimately for the purpose of predicting power; thus, assessing the quality of wind speed predictions should link speed and power (Lange 2005; Lange and Focken 2005).”
From probabilistic forecasts to statistical scenarios of short-term wind power production (2009, background): “Probabilistic predictions can be either derived from meteorological ensembles [5], based on physical considerations [6], or finally produced from one of the numerous statistical methods that have appeared in the literature, see [4, 7, 8, 9, 10] among others.”
Current methods and advances in forecasting of wind power generation (2012, positive): “The process of downscaling involves the production of more detailed spatial information from coarse NWP outputs using physical and/or statistical models [17].”
Current status and future advances for wind speed and power forecasting (2014, methodology): “The physical approach to forecasting, in contrast to statistical approach, uses the detailed physical description to model the onsite conditions at the location of the wind farm [7, 30].”