Signals from the energy edge.
Notes on utility data, trustworthy systems, interoperability and the grid. How we think about the hard parts, and what we're building.
ASHRAE Level 2 energy audit: what it includes and what data it needs
An ASHRAE Level 2 energy audit under Standard 211 adds an end-use breakdown and costed measures to a Level 1. What it delivers, who requires it, and the utility data to have ready.
Utility bill automation: what it covers, and what to look for
Utility bill automation covers five stages: collection, extraction, validation, workflow and delivery. A buyer's guide to what good looks like at each, with a vendor checklist.
Automated utility invoice validation: what it checks, and how it works
Automated utility invoice validation runs a fixed set of checks on every bill before payment: arithmetic, tariff, meter reads, periods, duplicates, demand. What each one catches.
Extracting utility data across mixed commodities at portfolio scale
One bill is easy to read by hand. A portfolio of electricity, gas, water and steam across hundreds of formats is a different problem. Here is why mixed-commodity extraction breaks templates and OCR, and what it actually requires.
Putting Green Button interval data to work: demand management and cost allocation
The monthly bill tells you what you used, not when. Interval data is the when, and Green Button makes it portable. Here is how to turn it into lower demand charges and fair cost allocation.
What "clean, structured utility data" actually requires
Everyone says they want clean utility data. Few can define it in a way another person could check. Here are the specific, testable properties that separate data you can trust from data that just looks tidy.
Energy data for cold storage and food and beverage sites
Refrigerated warehouses and food plants are among the most energy-intensive facilities there are. Here is how to collect and benchmark the data behind them.
Energy data management for logistics and warehousing
Warehousing and distribution portfolios have distinctive load profiles and big demand charges. Here is how to collect and use the utility data behind them.
Designing an energy data pipeline from ingestion to insight
The stages, layers, and roles that move utility bills and interval data from raw sources to trusted dashboards, forecasts, and reports.
Energy data governance for multi-site organizations
How large portfolios keep utility data consistent across sites, utilities and commodities: ownership, definitions, quality rules, lineage and access.
Collecting Scope 3 energy data from suppliers and tenants
Value-chain emissions dominate most footprints, yet the energy data sits with suppliers and tenants. Here is how to collect it for credible Scope 3 reporting.
Water and waste in corporate ESG reporting: beyond carbon
ESG disclosure now reaches water and waste, not just carbon. Here is what CDP, GRI and ESRS expect, and how to get the utility data behind it.
California SB 253 and SB 261: getting your energy data ready
SB 253 and SB 261 reporting is live for 2026. Here is how to get utility and energy data ready for CARB's scope 1, 2 and 3 disclosure deadlines.
CSRD first reporting cycle: what energy and building teams learned
The first CSRD sustainability statements are filed and the Omnibus reset the scope. Here is what energy and building teams learned about the data behind ESRS E1.
Demand ratchet clauses: how one peak inflates a year of bills
A ratchet clause sets your billed demand from a past peak, so one bad spike can raise your charges for months. Here is how ratchets work and how to spot one.
Unbundled vs bundled utility rates: what each model hides
Bundled rates fold every cost into one number. Unbundled rates split them apart. Each choice changes what you can see, verify, and manage on a utility bill.
Load factor: how the shape of your demand drives cost
Load factor measures how evenly a facility uses power, and it quietly sets your effective price per kilowatt-hour. Here is how to read it and why it matters.
Coincident peak and capacity charges explained
Capacity and coincident peak charges are set by your demand during a few grid peak hours, then billed all year. Here is how they work and why they surprise finance teams.
Detecting anomalies in energy consumption data
Baseload creep, equipment left on, after-hours spikes, and meter faults hide in your interval data. Here is what an energy anomaly is, the simple detection methods practitioners actually use, and why clean, complete data comes first.
Connecting utility data to your energy tools: one clean dataset, many destinations
Energy teams feed utility bills and interval data into benchmarking, feasibility, BI, and emissions tools. The real bottleneck is getting clean, standardized data out of many utilities first. Here is how the shared foundation works.
Building energy and utility dashboards in Power BI from utility data
A practical guide for Canadian energy and facility teams: how to model meter and bill data, avoid the garbage-in problem, choose refresh options, and build Power BI measures that hold up.
Automating ENERGY STAR Portfolio Manager: keeping utility data current
Portfolio Manager scores are only as good as the monthly meter data behind them. Here is how to keep every meter, every month, current without hand keying bills across a portfolio.
Using utility data in RETScreen: getting clean, complete consumption and cost data ready to import
RETScreen Expert only works as well as the utility data you feed it. Here is what the performance analysis and M&V module needs, why weather normalization and a clean baseline matter, and how to stop hand-keying numbers off bills and portals.
Energy data for hospitals and healthcare facilities
Why healthcare runs so energy intensive, and how to track, benchmark, and weather-normalize energy across a hospital and clinic portfolio using clean, validated utility data.
Page 2 of 7 · 146 articles