zCFD performs positively in a wind energy blind test
Our CFD solver, zCFD, performed successfully in a recent blind test for the wind energy sector with only 2% difference between the real-world data and simulated data. The test used SCADA (supervisory control and data acquisition) data from the energy supplier, SSE, and its Greater Gabbard offshore wind farm.
This opportunity to put zCFD to the test with wind farm data derived from our involvement in SWEPT 2 (Simulated Wake Effects Platform for Turbines). One of the objectives of this three-year project was to develop, validate and benchmark zCFD as an advanced tool for modelling aerodynamic wake interactions in both onshore and offshore wind farms.
There were multiple partners involved in SWEPT 2 alongside Zenotech: SSE, DNV-GL, CFMS, ORE Catapult, STFC and the universities of Bristol, Surrey, Strathclyde and Imperial College London. SWEPT 2 concluded at the end of April 2018, and towards the end of the project, SSE offered to provide SCADA data related to power production from its Greater Gabbard wind farm in order to allow us to perform a blind test of our CFD code.
We were excited to have this opportunity to demonstrate the effectiveness of zCFD. Blind testing is a useful way to benchmark our product as the simulation data (CFD) is produced before having visibility of the real-world SCADA data and therefore the results cannot be skewed.
The analysis revealed an actual match between the simulated and real world data with only around 2% difference. This blind test demonstrates that users can place confidence in the use of the zCFD software and that it offers an effective way to help optimise future wind farms. The entire data set was produced in six hours, making use of cloud HPC via our comparator product, EPIC.
Dr Paul Housley from SSE said:
“zCFD performed well in predicting turbine interactions and wake losses at Greater Gabbard offshore wind farm in a blind test of its modelling capabilities.”
We are strong advocates for the increased and better use of real world data to inform and improve simulation tools used in the development of wind farms. The need for this is reinforced in the Government’s Industrial Strategy; it outlines the challenge of cleaner growth, citing one report that indicates that the UK’s clean economy could grow at four times the rate of GDP, while AI and machine learning is set to transform business processes by deploying huge datasets.
This effective blind test and the SWEPT 2 project show the validity of using SCADA or LIDAR (light-detection and ranging data) and in-service data from wind energy with advanced simulation tools to optimise wind energy performance.
Find out more about zCFD and get in touch to discuss how it could help your business or organisation.