Heating Consumption Optimisation
Description
The Heating Consumption Optimisation service analyses thermal energy consumption within the Torrelago district heating network to identify inefficiencies, detect anomalous consumption patterns (including elevated return temperatures and abnormal demand during mild conditions), and optimise heat distribution across connected buildings. Using statistical analysis, contextual peak detection, and AI models (LSTM, XGBoost), the service provides actionable insights for energy efficiency improvements.
More about the service
Business Need
The Torrelago DHN operates under varying seasonal conditions and serves multiple residential buildings with heterogeneous consumption profiles. Without systematic analysis, inefficiencies such as elevated return temperatures, unexpected consumption spikes, and gradual performance deterioration go undetected until they manifest in operational costs. The service provides the analytical foundation for data-driven operational improvements.
Key Performance Indicators
Accuracy in identifying abnormal peaks and inefficient behaviour vs. known historical events
Reduction of false positives through contextual detection methods
Ability to detect recurring anomalous patterns across different seasonal windows
Estimated potential energy savings associated with identified inefficiencies
Data Provided
Preliminary identification of anomalous consumption peaks and periods of abnormal behaviour
Estimation of optimisation potential with areas for energy reduction
Simplified energy consumption forecasts based on outdoor temperature
Historical data range: 2020-2024; 7-day rolling window contextual analysis