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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Miranda, M.S. Dunn, R.W. |
| Copyright Year | 2006 |
| Description | Author affiliation: Dept. of Electr. Eng., Univ. of Bath (Miranda, M.S.; Dunn, R.W.) |
| Abstract | The contribution of wind power in market-driven power systems together with the uncertain nature of the wind resource have led to many research efforts on methodologies to predict future wind speed/power production. Applications such as the operational balancing market in the UK would benefit from accurate one-hour-ahead forecasts of the available power from all generators, wind being no exception. This paper focuses on one-hour-ahead wind speed prediction using a Bayesian approach to characterise the wind resource. To test the approach, two years of wind speed data from a weather station were modelled as an autoregressive process. In this paper, the methodology used is described together with the model employed and prediction results are presented and compared to the persistence method. The results obtained indicate that Bayesian inferencing can be a useful tool in wind speed/power prediction, particularly due to the flexibility inherent to the methodology |
| File Size | 342629 |
| File Format | |
| ISBN | 1424404932 |
| DOI | 10.1109/PES.2006.1709479 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2006-06-18 |
| Publisher Place | Canada |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Wind speed Bayesian methods Wind forecasting Weather forecasting Wind energy Power systems Production systems Economic forecasting Power generation Wind energy generation wind energy Bayesian inferencing Markov chain Monte Carlo simulation prediction methods short-term wind forecast statistical methods |
| Content Type | Text |
| Resource Type | Article |
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