AI Utilities Tariff Optimization System Development
Utility tariffs are a complex multi-parametric system with seasonal and temporal patterns. An AI system analyzes consumption, predicts load, and optimizes resource distribution to reduce costs while maintaining service levels.
Use Cases
Management Companies and HOAs: Heat, water, and electricity consumption forecasting by building. Optimal planning of energy resource procurement. Leak detection and anomalous consumption detection.
Industrial Enterprises: Optimization of electricity consumption considering tariff zones (peak/night). Peak shaving — reducing consumption peaks to lower declared power capacity.
Smart Buildings: Automatic HVAC, lighting, and elevator control based on predicted load.
Technical Stack
Demand Forecasting: Prophet / TFT on historical consumption data (minimum 2 years). Considerations: weather (OpenWeatherMap API), calendar (workdays/weekends, holidays), events. MAPE 5–12% for daily forecast.
Anomaly Detection: Isolation Forest for detecting anomalous consumption. Alert on deviation >2σ from normal — potential leak or malfunction.
Tariff Optimization: Linear Programming (scipy.optimize, PuLP) for optimal consumption planning within tariff constraints. What to consume at night (cheaper), what during day.
Integration: SCADA systems via OPC-UA or Modbus protocols. Meters with AMI interface.