The CygNet Energy Load Forecasting (ELF) system is an application integrated with the CygNet SCADA system for forecasting natural gas load demand. ELF uses neural networks to model the complex relationships between known environmental, economic, and social variables, like the weather and the date. The effect of these variables on customer demand for natural gas is then used to forecast energy load for a user-defined entity (meter, group of meters, facility) so that contractual obligations (demand capacity) can be met.
CygNet uses a configuration, training, and forecasting engine in the UIS to import historical gas load data, forecast gas load data, historical input data, and forecast input data, and to store that data into CygNet. The forecasting engine uses this data to perform neural network definition training and energy load forecasting tasks.
Once causal relationships are identified, CygNet uses the accumulated historical gas load data to establish the nature of the causal relationships, as well as adequate forecasted information, and estimates their effect on customer demand for natural gas.
More:
Energy Load Forecasting Overview
Understanding the CygNet ELF Import Schema
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