2016

Project Start Date

01st Jun 2016

2016

Project End Date

30th Nov 2016

High-Resolution Solar and Wind Energy Datasets for Ireland

High-resolution datasets for use in renewable energy applications

Overview

The aim of this project was to produce and make available, long-term, high-resolution gridded datasets of solar radiation and wind energy (onshore and offshore) fields for Ireland.

The climate of Ireland was simulated by downscaling ECMWF ERAInterim global data using the following Numerical Weather Models (NWPs):

  • ICHEC WRF with 2-km grid spacing
  • ICHEC COSMO-CLM5 with 1.5-km grid spacings

Each simulation covers the period 1981-Present and fields are archived at one-hour intervals. The NWP simulations were carried out as part of an Environmental Protection Agency (EPA) funded project. Figure 1 presents wind speed, air density and wind power at 60m, 120m and 180m heights.

 

Mean Wind Speed, Air Density and Wind Power (1981-2015)
Figure 1. COSMO-CLM5 1.5km resolution wind data. The columns contain mean wind speed, air density and wind power for the period 1981-2015 at 60m, 120m an180m height.

 

The datasets were post-processed so that end-users can easily access and manipulate the data. For example, a Weibull probability density distribution was fitted to the hourly, monthly, seasonal and annual wind speed time series (1981-2016) at each grid-point at heights 20m, 40m,.., 200m. The Weibull datasets allows the end-user to simply calculate derived statistics as opposed to analysing the entire dataset. Figure 2 presents the probability of an “energetically useful wind speed” (i.e., between turbine cut-in and cut-out value of 3 and 25 m/s, respectively) as derived from the Weibull parameters. Results are presented at heights of 20, 80 and 140m. The datasets were also post-processed so that a wind rose at a user defined height and location can be easily calculated. These post-processed datasets reduced the size of the datasets from 50TB to 10GB and reduces the time required to produce useful statistics from days to seconds.

The methods developed through the SEAI-funded project are being applied to a current EPA-funded project which involves analysing and promoting the recently completed Met Éireann reanalysis (MÉRA) simulation of Ireland.

 

Probability of an energetically useful wind speed (1981-2015)
Figure 2. Probability of a wind speed occurring between 3 and 25 m/s as derived from the Weibull parameters; (a) 20m height, (b) 80m height and (c) 140m height. In each case, the COSMO-CLM data are considered for the period 1981-2015.

 

It is expected that applications of the datasets will include an update of the SEAI wind atlas and the development of a first solar atlas for Ireland. A solar atlas will allow for policy makers, industry and the general public to make informed decisions on the cost-effectiveness of solar energy installations (see Figure 3). In addition, the datasets will be shared with industry and third level institutes and hence promote wind and solar energy research and development in Ireland.

The research and resulting datasets will underpin and support Ireland's climate change commitments such as the COP21 targets and the EU Directive on the Promotion of the Use of Renewable Energy (2009/28/EC, NREAP), whereby Ireland is committed to ensuring that 16% of the total energy consumed in heating, electricity and transport is generated from renewable resources by 2020.

 

Simulated Solar Energy Datasets (1981-2015)
Figure 3. Potential solar energy and agriculture applications; (a) mean daily sunshine duration, (b) average surface net downward shortwave radiation for the period 1981-2000.

 

This SEAI funded work has seen ICHEC nominated as a finalist for Best Contribution to Data Science from an Academic Research Body in the data Science Awards 2017.

If you are interested in learning more about the project or obtaining datasets, please contact paul.nolan@ichec.ie

€64,000
Project funding
6
Funded Person Months