About
Abriliam Consulting is a Canadian energy analytics practice specializing in industrial and commercial facility performance — turning operational data into measurable savings and defensible engineering decisions.
What We Do
We work at the intersection of mechanical systems engineering and data science. Our projects typically start with messy operational data — BAS trend logs, utility billing records, SCADA exports, weather files — and produce actionable analysis: savings estimates, M&V frameworks, predictive models, and capital planning tools grounded in engineering fundamentals.
Chiller & Refrigeration Plant Analytics
Performance diagnostics, low delta-T syndrome identification, hydraulic regime detection, cooling tower analysis, and plant-level efficiency optimization using trend data and thermodynamic modeling.
Energy Conservation Measure Analysis
Prospective savings estimation and post-implementation M&V aligned with IPMVP — including floating head pressure, VFD retrofits, condenser optimization, and controls upgrades across commercial and industrial refrigeration.
Electricity Cost Optimization
Machine learning-driven peak demand prediction, Global Adjustment optimization for Ontario Class A customers, and load curtailment strategy development using IESO market data and weather-driven forecasting.
Portfolio-Level Building Analytics
Degree-day regression screening across large building portfolios, thermal performance benchmarking, and data-driven prioritization of envelope and mechanical retrofits using utility billing data.
Approach
Every project starts with engineering fundamentals — thermodynamics, heat transfer, fluid mechanics — and uses data to quantify what the physics predicts. We don't fit models to data without understanding why the relationship exists. When a regression slope tells us something about a building's thermal performance, we can trace it back to the steady-state heat loss equation. When a gradient boosting model predicts peak demand, the SHAP feature importance should align with what an experienced energy manager already knows about weather-driven cooling loads.
Our deliverables are reproducible. Analysis is built in Python and Jupyter notebooks with documented methodology, version-controlled code, and transparent assumptions. Clients receive not just results, but the analytical framework — so the work can be verified, extended, and rerun as conditions change.
Technical Toolkit
Sectors
Industrial manufacturing, commercial refrigeration and cold storage, institutional facilities, municipal building portfolios, and Ontario electricity market participants. Our experience spans the mechanical systems and energy cost structures common to facilities in the 500 kW to 20 MW demand range.
Interested in working together?
We take on project-based engagements in energy analytics, savings verification, and predictive modeling.
Get in Touch