As promised in my last blog, in this blog I wish to share how Volume issue of Vestas Wind System’s was solved usinga Big Data implementation.
- Vestas Wind Systems offers its wind turbine products as alternative energy solutions in a competitive market that is exploding in terms of demand, and characterized by extremely competitive pricing.
- Wind turbines are a multi-million dollar investment with a lifespan of 20 to 30 years. The location chosen to install and operate a turbine can greatly impact the amount of power generated by the unit, as well as it how long it is able to remain in operation.
- In order to determine the optimal placement for a turbine, a large number of location-dependent factors must be considered including temperature, precipitation, wind velocity, humidity, and atmospheric pressure.
- The prior state of the art of location determination – took weeks of data analysis;
- Using more, in fact all, of the available data will improve the effectiveness of the placement process. Current solution had the ability to only leverage a fraction of the data.
- The solution currently analyzes 2.6 PB of data with the expectation that it will grow to 6 PB over the next few years.
Benefits reaped by Big Data implementation
- Reduced response time for wind forecasting information by approximately 97 %—from weeks to hours—to help cut development time
- Lowered the cost to customers per kilowatt hour produced and increased customers’ return on investment
- Reduced IT footprint and costs, and decreased energy consumption by 40 %—all while increasing computational power
“We can give customers much better financial warrantees than we have been able to in the past and can provide a solid business case that is on par with any other investment that they may have.” — Lars Christian Christensen, Vice President, Vestas Wind Systems A/S