A vector auto-regressive model for onshore and offshore wind synthesis incorporating meteorological model information

摘要

The growth of wind power production in the electricity portfolio is strivingto meet ambitious targets set, for example by the EU, to reduce greenhousegas emissions by 20% by 2020. Huge investments are now being made in newoffshore wind farms around UK coastal waters that will have a major impacton the GB electrical supply. Representations of the UK wind field insyntheses which capture the inherent structure and correlations betweendifferent locations including offshore sites are required. Here, VectorAuto-Regressive (VAR) models are presented and extended in a novel way toincorporate offshore time series from a pan-European meteorological modelcalled COSMO, with onshore wind speeds from the MIDAS dataset provided bythe British Atmospheric Data Centre. Forecasting ability onshore is shown tobe improved with the inclusion of the offshore sites with improvements of upto 25% in RMS error at 6 h ahead. In addition, the VAR model is usedto synthesise time series of wind at each offshore site, which are then usedto estimate wind farm capacity factors at the sites in question. These arethen compared with estimates of capacity factors derived from the work ofHawkins et al. (2011). A good degree of agreement is establishedindicating that this synthesis tool should be useful in power system impactstudies.