AI Carbon Accounting Automation
Automated carbon accounting and ESG reporting using AI
The Problem
“Automate carbon accounting across complex energy operations”
Organizations face these key challenges:
Fragmented, inconsistent data across assets (CEMS, SCADA, fuel logs, utility bills, shipping, and procurement) leading to manual reconciliation and delayed close
High uncertainty and frequent errors from spreadsheet-based calculations, inconsistent emission factors/GWPs, and unclear boundaries (equity share vs operational control)
Audit and compliance risk due to weak traceability, limited documentation of assumptions, and changing regulatory requirements (GHGRP, ETS, CSRD/ESRS, customer emissions reporting)
Impact When Solved
Real-World Use Cases
AI Applications in the Energy Sector (from multiresearchjournal.com article)
Think of this as giving power plants and grids a smart brain that constantly watches operations, predicts future demand and equipment issues, and suggests optimal ways to run everything more safely and cheaply.
Artificial Intelligence for Energy Systems
Think of this as a playbook of AI tricks for running power systems—generation, grids, and consumption—more like a smart thermostat and less like a manual on/off switch. It applies machine learning to decide how much power to produce, when to store it, and how to route it so the overall system is cheaper, cleaner, and more reliable.