ecpEnergyTwinEvaluation

Welcome to the Energy Twin (ET) extension for SkySpark. Energy Twin is a machine learning-based SkySpark extension for energy data analysis and prediction.

Energy Twin libraries available on StackHub:

• ET Analytics
  • advanced ML library using detailed models with up to 15min sampling
  • ideal for building electrical energy consumption analysis and prediction
  • anomaly detection - predefined Sparks
  • tailored KPIs
  • based on the TOWT model by LBNL
  • free to download, licensed by ET Core
• ET Interactive
  • simple to use regression analysis using degree-days models and ASHRAE change point models
  • interactive model tuning and outlier removal
  • perfect for heat consumption analysis
  • free to download, licensed by ET Core
• ET Core
  • core mathematical modeling algorithms referenced by both ET Analytics and ET Interactive
  • ET licensing mechanism for both ET Analytics and ET Interactive
• ET Evaluation
  • additional tool for ET models’ prediction evaluation
  • free to download, operates only with models from ET Analytics and ET Interactive
• ET Common Tools
  • necessary package containing common functions used by all extensions

See the ET website for case studies and more information: Energy Twin webpage.