Turbines at this wind farm north of Limon, Colorado, collect and transmit massive amounts of data. <\/p>\n
Big data and artificial intelligence are producing ultra-accurate forecasts that will make it feasible to integrate much more renewable energy into the grid. <\/p>\n
Ultra-accurate forecasting of wind and solar power. <\/p>\n
Dealing with the intermittency of renewable energy will be crucial for its expansion. <\/p>\n
Wind power is booming on the open plains of eastern Colorado. Travel seven miles north of the town of Limon on Highway 71 and then head east on County Road 3p, a swath of dusty gravel running alongside new power lines: within minutes youll be surrounded by towering wind turbines in rows stretching for miles. Three large wind farms have been built in the area since 2011. A new one is going up this year. <\/p>\n
Every few seconds, almost every one of the hundreds of turbines records the wind speed and its own power output. Every five minutes they dispatch data to high-performance computers 100 miles away at the National Center for Atmospheric Research (NCAR) in Boulder. There artificial-intelligence-based software crunches the numbers, along with data from weather satellites, weather stations, and other wind farms in the state. The result: wind power forecasts of unprecedented accuracy that are making it possible for Colorado to use far more renewable energy, at lower cost, than utilities ever thought possible. <\/p>\n
The amount of wind power has more than doubled since 2009. <\/p>\n
The forecasts are helping power companies deal with one of the biggest challenges of wind power: its intermittency. Using small amounts of wind power is no problem for utilities. They are accustomed to dealing with variabilityafter all, demand for electricity changes from season to season, even from minute to minute. However, a utility that wants to use a lot of wind power needs backup power to protect against a sudden loss of wind. These backup plants, which typically burn fossil fuels, are expensive and dirty. But with more accurate forecasts, utilities can cut the amount of power that needs to be held in reserve, minimizing their role. <\/p>\n
Before the forecasts were developed, Xcel Energy, which supplies much of Colorados power, ran ads opposing a proposal that it use renewable sources for a modest 10 percent of its power. It mailed flyers to its customers claiming that such a mandate would increase electricity costs by as much as $1.5 billion over 20 years. <\/p>\n
But thanks in large part to the improved forecasts, Xcel, one of the countrys largest utilities, has made an about-face. <\/p>\n
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Smart Wind and Solar Power<\/a><\/p>\n","protected":false},"excerpt":{"rendered":" Turbines at this wind farm north of Limon, Colorado, collect and transmit massive amounts of data. Big data and artificial intelligence are producing ultra-accurate forecasts that will make it feasible to integrate much more renewable energy into the grid. Ultra-accurate forecasting of wind and solar power Continue reading