Energy load forecasting for natural gas pipeline operators

CygNet Software’s neural net-based software takes guess work out of energy load forecasting.

CygNet Software has extended its enterprise operations platform (EOP) for the oil and gas industry with a new energy load forecasting (ELF) module for natural gas pipeline operators. ELF uses a ‘self learning’ neural network to provide accurate predictions of future gas demand. ELF’s neural nets compare user-defined variance with actual values to compute load calculations. Neural net training can be farmed out to a server farm for better performance.

ELF maximizes profitability while respecting regulatory constraints and contractual obligations. ELF adjusts line pack and stored gas automatically, preparing pipelines for anticipated demand—taking the ‘guess work and grunt’ out of daily load planning. ELF extends CygNet EOP with transparent sharing of operational data. CygNet VP Steve Robb said, ‘ELF offers an out-of-the-box solution that lets pipeline operators deploy tools to automate daily operations and efficiently capture, manage and distribute data.’ EOP provides unified data management with a specific schema for gas pipelines and a gateway to leading enterprise service buses including TIBCO, BEA and Oracle. More from

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