Grid stability thanks to precise forecasts
A self-learning software system from Siemens can stabilize power grids. The program, which is based on neural networks, can forecast the electrical output of renewable energy sources over a 72-hour period with more than 90 percent accuracy. The data helps grid operators calculate power demand in their networks and fairly exactly order the amount of additional electricity required in advance. As reported by the magazine "Pictures of the Future", Siemens's global Corporate Technology (CT) research department developed the forecast software for Swissgrid in Switzerland....
Published By: PhysOrg - Monday, 11 June, 2012
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