Author
Henrik Aalborg Nielsen
Bio: Henrik Aalborg Nielsen is an academic researcher from Technical University of Denmark. The author has contributed to research in topics: Wind power & Wind speed. The author has an hindex of 23, co-authored 54 publications receiving 2860 citations.
Topics: Wind power, Wind speed, Population, Consensus forecast, Quantile
Papers published on a yearly basis
Papers
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TL;DR: In this paper, a two-stage method is proposed to forecast hourly values of solar power for horizons of up to 36 h. The results indicate that for forecasts up to 2 hours ahead, the most important input is the available observations of PV power, while for longer horizons numerical weather predictions (NWPs) are the more important input.
629 citations
01 Jan 2011
TL;DR: The method is suited to online forecasting in many applications and in this paper it is used to predict hourly values of solar power for horizons of up to 36 h, where the results indicate that for forecasts up to 2 h ahead the most important input is the available observations ofSolar power, while for longer horizons NWPs are theMost important input.
Abstract: This paper describes a new approach to online forecasting of power production from PV systems. The method is suited to online forecasting in many applications and in this paper it is used to predict hourly values of solar power for horizons of up to 36 h. The data used is 15-min observations of solar power from 21 PV systems located on rooftops in a small village in Denmark. The suggested method is a two-stage method where first a statistical normalization of the solar power is obtained using a clear sky model. The clear sky model is found using statistical smoothing techniques. Then forecasts of the normalized solar power are calculated using adaptive linear time series models. Both autoregressive (AR) and AR with exogenous input (ARX) models are evaluated, where the latter takes numerical weather predictions (NWPs) as input. The results indicate that for forecasts up to 2 h ahead the most important input is the available observations of solar power, while for longer horizons NWPs are the most important input. A root mean square error improvement of around 35% is achieved by the ARX model compared to a proposed reference model.
585 citations
TL;DR: An existing wind power forecasting system (Zephyr/WPPT) is considered and it is shown how analysis of the forecast error can be used to build a model of the quantiles of the Forecast Error, whereby the model obtained can beused for providing situation-dependent information regarding the uncertainty.
Abstract: For operational planning it is important to provide information about the situation-dependent uncertainty of a wind power forecast. Factors which influence the uncertainty of a wind power forecast include the predictability of the actual meteorological situation, the level of the predicted wind speed (due to the non-linearity of the power curve) and the forecast horizon. With respect to the predictability of the actual meteorological situation a number of explanatory variables are considered, some inspired by the literature.The article contains an overview of related work within the field. An existing wind power forecasting system (Zephyr/WPPT) is considered and it is shown how analysis of the forecast error can be used to build a model of the quantiles of the forecast error. Only explanatory variables or indices which are predictable are considered, whereby the model obtained can be used for providing situation-dependent information regarding the uncertainty. Finally, the article contains directions enabling the reader to replicate the methods and thereby extend other forecast systems with situation-dependent information on uncertainty. Copyright © 2005 John Wiley & Sons, Ltd.
255 citations
TL;DR: An overview of the different methods used today for predicting the power output from wind farms on the 1-2 day time horizon is given in this article, where the authors describe the general set-up of such prediction systems and also give examples of their performance.
Abstract: This article gives an overview of the different methods used today for predicting the power output from wind farms on the 1–2 day time horizon It describes the general set-up of such prediction systems and also gives examples of their performance Copyright © 2003 John Wiley & Sons, Ltd
193 citations
TL;DR: In this article, a grey-box approach is used to identify a model linking the heat consumption to climate and calendar information, where the process of building a model is split into a theoretical based identification of an overall model structure followed by data-based modelling, whereby the details of the model are identified.
151 citations
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TL;DR: The analysis of time series: An Introduction, 4th edn. as discussed by the authors by C. Chatfield, C. Chapman and Hall, London, 1989. ISBN 0 412 31820 2.
Abstract: The Analysis of Time Series: An Introduction, 4th edn. By C. Chatfield. ISBN 0 412 31820 2. Chapman and Hall, London, 1989. 242 pp. £13.50.
1,583 citations
TL;DR: An overview of forecasting methods of solar irradiation using machine learning approaches is given and it will be shown that other methods begin to be used in this context of prediction.
1,095 citations
TL;DR: A review of the current methods and advances in wind power forecasting and prediction can be found in this article, where numerical wind power prediction methods from global to local scales, ensemble forecasting, upscaling and downscaling processes are discussed.
1,017 citations
TL;DR: In this paper, a review article aims to explain the complexity of available solutions, their strengths and weaknesses, and the opportunities and threats that the forecasting tools offer or that may be encountered.
1,016 citations
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TL;DR: In this article, a review article aims at explaining the complexity of available solutions, their strengths and weaknesses, and the opportunities and treats that the forecasting tools offer or that may be encountered.
Abstract: A variety of methods and ideas have been tried for electricity price forecasting (EPF) over the last 15 years, with varying degrees of success. This review article aims at explaining the complexity of available solutions, their strengths and weaknesses, and the opportunities and treats that the forecasting tools offer or that may be encountered. The paper also looks ahead and speculates on the directions EPF will or should take in the next decade or so. In particular, it postulates the need for objective comparative EPF studies involving (i) the same datasets, (ii) the same robust error evaluation procedures and (iii) statistical testing of the significance of the outperformance of one model by another.
1,007 citations