One of the more exciting fields in the energy sector is wind power. As renewables gain more exposure to the public, wind power carries distinct advantages over solar or hydroelectric, including greater cost-effectiveness and the ability to operate without constant sunlight, greatly increasing potential locations for farms. Still, the capability for harnessing the wind remains untapped for various reasons. One way to address this issue is to utilize big data in both unique and unexpected ways. From using weather predictions to understanding turbine formations, wind power can reap the rewards of custom BI solutions to best answer some of the more important questions regarding wind power and get the most out of generation and transmission.

Forecasting better power generation
Much like solar power, wind turbines rely heavily on favorable weather conditions in ideal locations to maximize power generation. Unlike solar, however, it's possible to work with less wind. Still, many power companies are apprehensive in using wind power precisely because its intermittent nature makes it less than reliable. In order to address this issue, energy companies are incorporating weather conditions when assessing how much electricity they gain from a given day, according to Energy Biz.

Wind turbines can benefit from descriptive analysis.Wind turbines can benefit from descriptive analysis.

The way it works is that wind conditions and forecasts are mixed in with turbine speeds to get an accurate picture of expected power generation for the course of a single day. With increasingly granular weather predictions based on historical data, climate variables and other factors, an energy company can assess how much electricity it can deliver to the grid and how much reserve power it will need at any given point. This will not only save it money but also improve customer service.

Creating stronger turbine performance
Another key factor is that wind speed alone doesn't necessarily determine power generation. The direction of the wind in the face of the turbine and gust duration are two of many factors that contribute to how much electricity a farm makes on a given basis. Turbine performance is also a factor, which depends on component degradation and state of repair. In order to address these variables, descriptive analysis assesses overall turbine strength.

NA Wind Power Magazine explained that collecting data on individual turbines can help determine which ones perform best in the current circumstances or in specific periods of time. From using this data, companies can build wind farms with maximum efficiency and performance. Energy companies can then have better control from using wind power as an alternative renewable energy source.

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