The National Grid wanted to find a way to accurately predict the degradation of their assets due to environmental exposure.
The project looked at characterizing weather exposure and degradation rates for more than 3,500 OHL assets across the UK. We generated tens of terabytes of information, processing it using our in-house, high-performance computing system, before analyzing it using a combination of high-resolution meteorology and big data statistical techniques. The results were then compared against 10 years of maintenance schedules and on-site observations.
Our approach accurately predicted more than 75% of all damage observed by National Grid engineers on OHL assets across the country. It’s now being used to optimize asset management strategies in order to increase system reliability and protect investment, saving them tens of millions of pounds a year.