KPIs for energy usage using counterfactual
By Aman Ahuja in Projects
January 1, 2014
The Data Guild helped develop and assess models and key performance indicators (KPIs) for energy usage. Designed methods to measure change after some event (causal inference) using counter-factuals, and corresponding uncertainty. Provided strategic direction and best practices related to code, machine learning systems, and parallelizing analysis.
- Benchmarked against the ASHRAE 14 definition of savings
- New definition of energy savings based on counterfactuals & building models
- Machine learning (ML) pipeline parallelization
- Technologies utilized: python and scikit tools, starcluster spot instances on AWS compute.
Aman designed the ML pipeline and parallelization, implementing the savings calculation at scale. I worked with the team to assess our new savings calculation against the benchmark standard.