Overview

Project Highlights:

  • The UK will see a large expansion of offshore wind farms in the next 15 years;
  • Climate change is likely to increase the number of extreme weather events which will have an impact on offshore wind farm loading and power output;
  • This project will involve the use of state-of-the-art models, and measured data to predict the effect that future extreme events will have on offshore wind farms. 

The EU has a binding target of 20% of energy to come from renewables by 2020, with an associated CO2 emissions reduction target of 20% (relative to 1990) and a 20% reduction on energy usage by the same date. This is the so-called 20/20/20 target. The UK’s target is for 15% of energy to be sourced from renewables by this date. For this target to be met, over 30% of electricity will need to be generated from renewables and it anticipated that 92TWh of this will come from wind power with 35TWh onshore and 57TWh offshore by 2020 [1].

Assuming a central scenario, 40GW of offshore wind power capacity could be installed by 2030 according to WindEurope [2]. At present 9GW of wind power have been installed onshore and 5.1GW offshore [3]. With the rapid UK expansion of offshore wind (Figure 1(a) shows Europe’s largest offshore, the London Array), it is critical to understand the long term impact that this power source will have on the electricity supply system. In particular, if there are more extreme events such as storms, this may have an impact on the electricity supply if large numbers of offshore wind farms shut down in high wind conditions. There has been research to consider historical long term variation in wind conditions [4] but future projections are very uncertain.

An example of an extreme event is shown in Figure 1(b) where a gust front associated with violent convective thunderstorm activity caused a rapid increase in wind speed from 5m/s to over 20m/s and subsequent reduction in the space of a few hours during a summer period. This would cause an offshore wind farm to go from virtually no output to full output and back in a very short space of time. This could cause problems in the future for European grid operators if such events were to increase in frequency in response to global climate change.

(a) The London Array offshore wind farm and (b) a synthetic aperture radar (SAR) image showing gust fronts in the North Sea during vigorous convective activity (thunderstorms) on 24th July 2007.

Methodology

This project will study historic and future projected offshore wind speed data to better understand future impacts on the variation in wind speed conditions driven by global climate change. It will make use of existing offshore wind speed data from masts, e.g. the NOAH meteorological mast owned by the Offshore Renewable Energy Catapult as well as public data from the Marine Data Exchange. It will also use remote sensing data from satellite observations such as Envisat and Sentinel 1 and 2.

Future scenarios will be investigated using future global climate projections such as the NEX Global Daily Downscaled Climate Projections [5]. This will be downscaled using the WRF mesoscale model to provide high resolution data for studying extreme wind speed phenomena that could impact offshore wind farms both in terms of output and structural loading. The overall aim is: to predict the impact that future extreme weather events will have on offshore wind farm loading and power output.

Objectives:

  • Analyse historic data (e.g. surface data, remote sensing data, global forecasting data, reanalysis datasets, etc.) to assess frequency and characteristics of extreme weather events;
  • Determine suitability of WRF for downscaling global datasets for the prediction of extreme events and adapt or modify if necessary;
  • Use future global climate datasets to drive the WRF model and predict the frequency and magnitude of future extreme events that may impact offshore wind farm sites;
  • Quantify the impact that present and future extremes will have on offshore wind farm loading, fatigue and power output.

Training and Skills

CENTA students are required to complete 45 days training throughout their PhD including a 10 day placement. In the first year, students will be trained as a single cohort on environmental science, research methods and core skills. Throughout the PhD, training will progress from core skills sets to master classes specific to CENTA research themes.

The student will be based in the Centre for Renewable Energy Systems Technology (CREST) to gain expertise in the climatological and engineering aspects of offshore wind energy. The Wind Power Research Group within CREST is part of the wider EPSRC Supergen Wind Hub who also provide training to new researchers in the wind energy arena, including long term environmental conditions. The student will gain skills in wind analysis of surface and remote sensing data and modelling of wind conditions using global and mesoscale models with a focus on future climate change impacts.

Timeline

Year 1: Compilation and analysis of existing datasets for assessing offshore resource, e.g. mast, reanalysis and remote sensing data.

Year 2:  Compilation of future global climate datasets for use in assessing future climate scenarios for offshore wind conditions. WRF downscaling simulations using future global climate datasets. Produce journal paper based on existing historic data.

Year 3: Assessment of impact on future wind conditions on offshore wind farm output and loading. Writing up and production of journal paper on future impacts of climate change on offshore wind farms.

Partners and collaboration (including CASE)

 This project will be in collaboration with the Offshore Renewable Energy (ORE) Catapult whose remit is to work with the offshore marine energy industry and academia to provide testing infrastructure facilities and expertise to reduce the cost of energy in the marine energy sector. CREST are already working with ORE Catapult through the Supergen Wind Hub and have an existing NERC CASE studentship with the Catapult to study the Marine Atmospheric Boundary Layer (MABL) and its impact on offshore wind farms.

This project will be a CASE award complementing the above studentship and the ORE Catapult will provide data and expertise in understanding the offshore resource and its impact on offshore wind power. The student will spend time at the ORE Catapult at Blyth as part of its developing strategy to better understand offshore met/ocean conditions.

Further Details

For further information about this project, please contact Prof Simon Watson (S.J.Watson@lboro.ac.uk) at CREST (http://www.lboro.ac.uk/research/crest/) and the Offshore Renewable Energy Catapult: https://ore.catapult.org.uk/.

For enquiries about the application process, please contact Lauren Curtis, Wolfson School of Mechanical, Electrical and Manufacturing Engineering, Loughborough University (L.E.Curtis@lboro.ac.uk).

Please quote CENTA when completing the application form: http://www.lboro.ac.uk/study/apply/research/.