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FORECAST THE FUTURE
THE ENERGY DEMAND

Challenge

Forecasting short-term demand is challenging. Operators have a fairly good understanding of normal daily and weekly variations; however, it´s more complicated to understand if the next hour will have higher or lower demand than “normal.” Throughout the grid, many sensors record data of actual usage. The sensors are strategically placed by operators based on years of experience, giving reasonably good indications of variations in the overall energy demand.

 

Data such as the rate, order of change, and the day and time are good indicators of what to expect in the next 1-2 hours. Unfortunately, this is too much information to monitor and act upon constantly.

Solution

With Intelecy, operators can create forecast models without prior coding experience. The machine learning models are trained on patterns from 1-2 years of historical data, continuously monitoring and forecasting, enabling operators to make better decisions.

Better utilization of raw materials

Balanced production and demand 

Process efficiency

OTHER CASES
POWER AND RENEWABLE ENERGY INDUSTRY: