Actionable insights to reduce emissions
Use case
Challenge
With today’s focus on the green energy transition, the industry faces stricter regulatory requirements to reduce emissions. One example is flue gas from waste-to-energy plants, where the emission of gasses might be high. Various methods are used to remove harmful gasses, such as scrubbing, but these are complex and costly processes that can be difficult to control.
Solution
With Intelecy, operators can create no-code forecast models that predict future emissions. Predictions from the models enable the operators to make early process adjustments, thus allowing them to remove the gasses. In addition, you can create anomaly models that alert the operator when the cleaning process does not work as expected.
Result
- Reduced emissions
- Reduced costs
- Increased efficiency
Other Power & Renewable Energy cases
Forecasting energy demand
By producing in an optimal balance between supply and demand, the energy plant will improve raw material utilization and increase production and distribution cost efficiency. Discover how forecast no-code machine learning models predict the future energy demand.
Early warning of critical assets
Seasonal variations in weather and temperature are difficult to predict and can cause major fluctuations and challenges related to asset health. Learn how multivariable no-code AI models are used for predictive maintenance to prevent costly and, in worst case, critical asset downtime.