By their very nature renewable energy sources are difficult to manage because of their high variability. Fossil fuels have provided dependable, deterministic energy for an extended period of time. Power grids have evolved to depend on high capacity, rapidly deployable power sources. The legacy of this is a centrally managed grid with limited flexibility, and control systems which are unable to optimize the use of renewables over fossil fuels.
Our software makes dynamic usage of renewable energy sources in smart grids possible. We have developed innovative technology leveraging new large scale sources of Internet of Things (IOT) data throughout the grid to enable optimal decisions to be made with respect to grid operations.
Our AI solutions are deployed on accelerated hardware (GPU/FPGA) at the edge of the utility network, and in the cloud (public or private). The decisions our software makes enables the grid to achieve energy savings by optimizing the usage of renewable energy in conjunction with new storage and distribution technologies.
Our decisions are derived from mining, analyzing and deriving the optimal actions in real time, and near real time. The resulting increased use of renewable energy in an optimized smart grid will lower the cost of energy by displacing fossil fuels, and will also reduce Greenhouse Gas (GhG) emissions associated with non-renewable power sources.