In Denmark the demand for reliable wind power predictions has become more and more urgent during the recent years. This development is driven by several factors:
1In relation to weather and wind power forecasting short-term prediction refers to pre-dictions with a horizon from 1 hour and up to 48 – 72 hours ahead.
• The rated power of the installed wind turbines has more than quadru-pled since 1994 and does now constitute a substantial fraction of pro-duction capacity for the conventional power plants. In the western part of Denmark, for instance, the wind turbines have at several occasions been close to covering the entire power demand during periods with low power load. Optimal exploitation of the transmission grid and produc-tion facilities in a system with this high a penetraproduc-tion of wind power will obviously require reliable predictions of the wind power production.
• A power exchange trade – NordPool – has been introduced between the Scandinavian countries. The ordinary power trading for the following day is finalized at noonday, hence for utilities with a high penetration of wind power reliable wind power predictions are a prerequisite for efficient trading on the NordPool.
• As a result of the ongoing liberalization of the electricity sector a new structure is emerging. The sector is being divided into three indepen-dent types of operators:
– The production companies which own and operate the conventional power plants and some of the wind farms.
– The transmission companies which own and operate the high volt-age transmission network. The responsibility for system reliability and endurance will typically belong to the transmission companies.
– The distribution companies running the low voltage distribution network supplying the individual consumers.
When the liberalization is fully implemented the power trading between the various operators will be based on short term contracts typically covering the following day. Any deviations from the reported demand or production will then carry an economical penalty. Thus operators with considerably amounts of wind power will have a clear interest in precise wind power predictions.
In the western part of Denmark, where the majority of the wind turbines are located, a large fraction of the wind turbines is privately owned and situated in small groups or standing alone. As a result on-line power measurements at the utilities have up to recently only been available for a minor fraction of the wind turbines in the western part of Denmark. For most of the remaining turbines the only information regarding their production has been in form of monthly or quarterly energy readings from their accounting meters. Within the last few years this has changed, though, as the changing market conditions require that the power measurements covering all wind turbines larger than 150 kW
are made available as 15 minute average values at the utilities responsible for the accounting for the area in question. The measurements are not available on-line but is delivered in diurnal batches with a delay of a few days.
The work on prediction of wind power was initiated as a cooperation between Elsam and IMM in 1992 under the project, Wind Power Prediction Tool in Control Dispatch Centres, sponsored by the European Commission. During this project the first version of WPPT was developed and implemented at Elsam’s control center at Fredericia. The prediction models in WPPT 1 utilized on-line measurements of wind power and wind speed. WPPT 1 went into operation in October 1994 and was subject to a three months trial period.
The experience gained as well as further details regarding the models and user interface developed can be found in (Madsen, Sejling, Nielsen & Nielsen 1995) and (Madsen, Sejling, Nielsen & Nielsen 1996). In short it became apparent that WPPT 1 was capable of providing the operators with useful predictions up to 8 to 12 hours ahead, but for larger prediction horizons further model development was needed.
In (Landberg, Hansen, Vesterager & Bergstrøm 1997), (Landberg 1997a) and (Landberg 1997b) physical models describing the wind farm layout and the influence of the surroundings are used in combination with meteorological forecasts of wind speed and direction to make predictions of power production with a horizon of up to 36 hours ahead. Promising results were found for the longer prediction horizons, but the approach had poor performance on shorter horizons.
In (Nielsen & Madsen 1997) it is proposed to utilize meteorological forecasts from the national weather service as input to the previously developed statis-tical prediction models. Nielsen & Madsen (1997) shows, that introduction of meteorological forecasts in the prediction models results in an improved performance for all prediction horizons and especially for the larger predic-tion horizons very distinct improvements are found. The results from (Nielsen
& Madsen 1997) are summarized in paper G. In 1997 a new project, Imple-menting short-term prediction at utilities, was initiated again with Elsam as partner and sponsored by the European Commission. The purpose of the project was to further refine the wind farm power prediction models and im-plement an operational wind power prediction system – WPPT 2 – at the control center of Elsam based on on-line measurements and meteorological forecasts for a number of reference wind farms in the western part of Den-mark. Predictions of power production for the individual wind farms as well as for the entire population of wind turbines in the area are calculated by the implemented system, where the latter is accomplished by means of an
upscaling algorithm. The developed models as well as the results obtained with respect to the wind farm predictions are described in (Nielsen, Madsen, Nielsen & Tøfting 1999), whereas qualitative and quantitative assessments of the predictions for the entire area are given in paper I and (Nielsen, Madsen
& Christensen 2000), respectively.
Up to 1999 most research focused on building the best possible power predic-tion models for wind farm, whereas the upscaling models only had received minor attention. This was due to lack of detailed information regarding the power production from wind turbines not covered by on-line measurements at the utilities. The appearance of accounting data made it possible to build more sophisticated upscaling models and in 1999 a new project Wind farm production predictor2 with IMM, Risø and all the major Danish power util-ities as partners was started. The purpose of the project was to develop a prediction system – Zephyr – for all wind turbines in a large area based on the available data – meteorological forecasts, on-line measurements for selected reference wind farms and accounting data covering almost all wind turbines in the area. The software implementation of Zephyr was a very ambitious multi-tier client server solution inspired by the Java Enterprise Beans architecture as described in (Giebel, Landberg, Joensen, Nielsen & Madsen 2000). The complicated architecture became the undoing of the first version of the Zephyr modelling system and in the end the development was abandoned. During the project new wind farm and upscaling model was developed – see (Nielsen, Madsen, Nielsen, Landberg & Giebel 2001, Marti, Nielsen, Madsen, Navarro
& Barquero 2001, Nielsen, Madsen, Nielsen, Giebel & Landberg 2002) and paper J – and these are currently under implementation in a revised version of the WPPT software. This new version – WPPT 4 – will also serve as the model engine in a comming re-implementation of the Zephyr system.