We Can Use Cell-Phone Towers to Forecast Wind Power
Photos: Onsemble/Flickr, CC.
Goal: Accurate Wind Forecasts
The more wind farms we build, the more our power grid will have to incorporate mechanisms to deal with the inherent variability of a wind farm's output. Part of that will probably be accomplished by having more long-distance transmission capacity and interconnecting regional grids, another part might come from demand response and real-time pricing, and being able to accurately forecast how much wind there will be hour by hour will also help to optimally use wind resources. This is the problem that wind data provider Onsemble is working on.
Photo: Flickr, CC
The company says that it now has sensors capable of tracking the wind data near 95 percent of the wind farms in Texas, and that its data is very accurate because it has put its sensors on cell phone towers (80-120 meters above the ground, unlike the ground-level stations used in most cases).
Using the real-time data from the sensors fed into its algorithm, forecasting predictions can be generated every 10 minutes. The determined behavior patterns and predictions for a given area can then be used by wind farm and grid operators to determine fluxes in available electricity.
The network includes 100 sensor hubs, placed strategically near wind farms throughout Texas, and will supply data to the Electric Reliability Council of Texas (ERCOT), which manages the electric grid for about 75 percent of Texas. (source)
This is a great way to use something that was already there (the cell towers), and if the wind forecasts can help wind farms being more productive and other power plants to be used more efficiently (if your forecasts are very accurate, you probably need to keep less backup power spinning), this should be done everywhere where there are wind farms and cell towers.
More on Alternative Energy
iSuppli Forecasts 15.8GW of Solar PV in 2010, 19.3GW in 2011
South-Korea to Invest $8.2B In Massive Offshore Wind Farms
Stirling Engine Made with Soda Cans Spins to 860 RPM (Video)
Algenol's Algae-to-Ethanol Delivers 67% to 87% Reduction in CO2
Dr. Steven Chu Answers Questions from Citizens About Energy Conservation (Video)
Should Energy Conservation be Framed in Terms of What Would be Lost?
2009 Snapshot of U.S. Energy Use by Lawrence Livermore National Laboratory