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[DSC Croatia 22] Reducing Carbon Footprint in Smart Buildings - Nemanja Milicevic

  1. Reducing Carbon Footprint in Smart Buildings CROATIA 2022
  2. 39% annual global CO2 emissions generated by buildings Source: Global status report 2018, EIA
  3. Source: Global status report 2018, EIA
  4. Heating Ventilatio n Air Conditioning
  5. Optimal energy consumption control for HVAC appliances
  6. 3rd party APIs Smart Buildings Load Forecasting Anomaly Detection Optimal Control
  7. Building Metadata Sensor Readings Weather Data Custom Integrations Ingestion Storage Machine Learning
  8. Anomaly Detection Missing Data Sensor Value Outliers Unavailable Data Sources
  9. Sensor Value Outliers Using Median Absolute Deviation (MAD) ■ Simple, robust method for outlier detection ■ Calculated for every important metric (indoor temperature, HVAC consumption, etc.) ■ Distinction between different parts of the day or week ■ Commonly used in time-series DBs (e.g. InfluxDB) ■ Threshold balances false positives and false negatives ■ Near-real time detection with Spark Streaming
  10. Load Forecasting ■ Hourly predictions ■ 31 features engineered from building metadata, sensors, and weather ■ 3M samples (2.4M train, 600k test) ■ 3 years of data from 100s of offices ■ Model robust to missing data R2 0.8971 RMSE 0.1943 MAE 0.0934 Feature Store Feature Store Feature Store Model Model Features Training Inference
  11. Optimal Control ■ Reinforcement Learning Agent (DQN and PPO) ■ Turns HVAC on/off based on user constraints ■ Three modes: - Optimal Comfort - Optimal Savings - Combined ■ Approach used in large data centers Historical Data Metadata User Rules Thermal Model Agent Environment Action Reward Rule: Every Monday from 9 am to 5 pm temperature should be between 22 and 26 degrees celsius
  12. Live Testing 7 bank offices in Portugal Optimal control for 4 weeks with user feedback 218k EUR total annual HVAC cost
  13. *between 20% and 35% energy savings depending on the office location 35%
  14. Challenges
  15. Integration Data Quality Pandemic Testing Partners
  16. This project has received funding from the European Union’s Horizon 2020 research and innovationprogramme under grant agreement No 779790
  17. Consistent small steps lead to impactful results