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This report outlines the key learnings Vestas has learnt in the period between April 2019 – October 2019.

Report extract

Since the previous lessons learnt report, three new self-forecasting models have been developed by Utopus, these are the SCADA+Weather model, SCADA+Met Mast model and the SCADA+Weather+Met Mast model. Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) analyses were carried out versus wind ranges and power ranges for each of the models to understand the strengths and weaknesses of each of the models. The analyses and findings have been described in detail under Lesson Learnt No 1.

Towards the end of last year, Vestas also completed the Met Mast installation project on behalf of Infigen, which included a new ‘Met Mast B’ with meteorological instrumentation and data logger, and the addition of a data logger on the existing ‘Met Mast A’. There were some challenges in terms of data transfer to the Vestas SCADA system and to Infigen’s independent met mast data service provider. These have been discussed in Lesson Learnt No 2.

Finally, in order to carry out the cost-benefit analysis of using the self-forecasting values instead of AWEFS, Infigen are developing a Causer Pays Factor (CPF) tool. Further details on the tool and its implications are described in Lesson Learnt No 3.

Last updated 07 July 2020
Last updated
07 July 2020
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