Energy consumption index generator

The Energy Consumption Index Generator, based on consumption data (electricity, gas, hot water, etc.) and contextual parameters (weather and climate indices, usable floor area, building use, occupancy, architectural layout, urban environment, etc.), will calculate a standardized index that enables the comparison of the energy efficiency of different public buildings.

This index is intended to:

• Classify and compare buildings according to their efficiency.

• Detect significant consumption deviations.

• Propose prioritized actions based on potential impact.

• Monitor the evolution of energy performance over time.

The tool should incorporate additional functionalities such as: segmentation by building typology, adjustment for different metrics (e.g., degree-days), graphical visualization, report export and automated alerts, readyness to integrate with GIS platforms and notification systems.

This benchmarking tool for public buildings will deploy the following functionalities:

 1. Data collection and aggregation of physical and operational information

• Import from the Infraestructures.cat data spaces.

• Import of complementary data from their specific sources.

• Flexible incorporation of documentary data in standard formats.

• Incorporation of synthetic data.

The architecture may include a climate normalization module, access to reference databases, and integration with existing energy monitoring or management platforms, whether proprietary or third-party.

 2. Normalization and adjustment

• Application of normalization parameters.

• Adjustment for seasonal and temporal variables, geographic and environmental factors, intensity of use, etc.

• Definition of energy consumption or performance index(es).

 3. Benchmarking

• Creation of internal references (percentiles, optimal ranges) and external references (regulations, best practice guides, sector benchmarks).

• Assignment of scores or labels based on the relative efficiency of each building.

• Internal benchmarking (between buildings of the same organization/type/region/...) and external benchmarking (comparison with sectorial or regional reference values).

The system will allow segmentation by facility type (schools, offices, sports centers, hospitals...), taking into account the specific consumption profiles of each use and establishing efficiency rankings.

4. Recommendations and alerts

• Anomaly detection algorithms: (a) unexpected consumption variations, or (b) sustained long-term deviations.

• Identification and proposal of energy efficiency improvement actions (e.g., improved insulation, HVAC optimization, awareness campaigns, etc.).

In addition to establishing efficiency rankings, the system will identify generic improvement measures based on various parameters (typology, location, etc.) and determine the potential improvement ranking of the buildings.

5. Reporting and visualization

• Interactive dashboard: bar charts, heat maps, and trend graphs showing monthly and annual evolution.

• Custom control panels for technicians and managers with key KPIs (consumption per m², cost €/m², CO₂ emissions).

• Reports for monitoring and decision-making.

• Automated export of reports and alerts, with transfer to GIS platforms and notification systems.

The system will therefore allow the generation of graphical visualizations and automated reports for objective and transparent result tracking; it will also generate and communicate alerts. Special attention will be paid to incorporating traceability and explainability of how outputs are produced.

6. Scalability and integration

• Modularity to incorporate new data sources.

• Integration with third-party facility management platforms and ERPs.