Digital use of satellite observations in offshore wind energy

Energy Research Accelerator

The Energy Research Accelerator (ERA) is a cross-disciplinary energy hub, fostering business-academia collaboration to accelerate solutions to global energy challenges. It will provide new buildings, skilled people, jobs products and services to transform the energy sector. Building on existing programmes and academic expertise across the partnership, universities within ERA have committed over £2m for doctoral students for the ERA skills agenda. Through Innovate UK, the government has committed a capital investment of £60m, and ERA has secured private sector co-investment of £120m. ERA’s priorities of Geo-Energy Systems, Integrated Energy Systems and Thermal Energy will help deliver new technologies and behaviours, enabling ERA to have a transformative effect across the energy spectrum.

ERA is a key programme within Midlands Innovation - a consortium of research intensive universities that harnesses the Midlands’ combined research excellence and industry expertise to tackle the biggest challenges facing the UK.

The Project:
Aim: To develop a data-based approach to evaluate offshore wind resources using satellite measurements.

Offshore wind farms have been flourishing and changing the coast line of the UK. In this era, it has become imperative to develop a capacity for accurate wind resource assessment, which is critical to wind farm layout and operations. The state-of-the-art wind resource assessment relies on meso-scale numerical simulations or reanalyses and fails to produce results accurate enough to inform decision making. This project aims at delivering a step changing in offshore wind resource assessment by developing novel algorithm and subsequently a numerical tool. The wind speed at 10 m above the sea level will be extracted from satellite SAR images and then projected to the wind-turbine height using atmosphere temperature distributions. A neural network will be established to estimate the relation between direct LiDAR/mast measurements and the output of this tool, and subsequently configure the algorithm/tool. This tool will be then tested applying SAR images collected from the Satellite Applications Catapult and