All Outputs (2)

Integrating wind variability to modelling wind-ramp events using a non-binary ramp function and deep learning models (2022)
Presentation / Conference
Sharp, R., Ihshaish, H., & Deza, J. I. (2022, August). Integrating wind variability to modelling wind-ramp events using a non-binary ramp function and deep learning models. Paper presented at International Conference for Sustainable Ecological Engineering Design for Society, SEEDS 22, UWE Bristol and online

The forecasting of large ramps in wind power output known as ramp events is crucial for the incorporation of large volumes of wind energy into national electricity grids. Large variations in wind power supply must be compensated by ancillary energy s... Read More about Integrating wind variability to modelling wind-ramp events using a non-binary ramp function and deep learning models.

Wind power ramp characterisation and forecasting using Numerical Weather Prediction and Machine Learning models (2021)
Presentation / Conference
Ihshaish, H., Deza, I., & Sharp, R. (2021, October). Wind power ramp characterisation and forecasting using Numerical Weather Prediction and Machine Learning models. Paper presented at Tackling Climate Change with Machine Learning: Workshop at NeurIPS 2021