Electricity Emissions Tracking With Real-Time Grid Mix Attribution
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Solution Overview
Problem
Existing methods for tracking Scope 2 emissions from purchased electricity are inaccurate due to reliance on long-term averages of grid mix, failing to account for real-time fluctuations in renewable energy sources, leading to imprecise carbon footprint calculations.
Innovation Solution
A computer-implemented method and system that surveils and monitors electricity production and consumption in real-time or near real-time, using local monitoring devices and smart energy meters, coupled with blockchain technology to track the green energy mix and attribute carbon footprints accurately to specific applications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If long-term average grid mix data is used for carbon footprint calculations, then calculation simplicity is improved, but measurement precision deteriorates
Solution Approach 1:
The system transitions from static long-term average grid mix data to dynamic real-time monitoring of grid mix composition. Smart meters and monitoring devices continuously track the proportion of renewable versus non-renewable energy sources, enabling carbon footprint calculations that reflect actual instantaneous grid conditions rather than historical averages.
Solution Approach 2:
The system implements continuous feedback loops where monitoring devices measure actual grid mix composition, this data is fed back to calculation systems, and adjustments are made to carbon footprint calculations in real-time. This closed-loop approach ensures calculations continuously reflect current grid conditions, resolving the inaccuracy introduced by using outdated average data.
2Measurement precision
If real-time monitoring of grid mix is implemented, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The system employs multi-functional smart meters and monitoring devices that simultaneously perform multiple tasks: measuring electricity consumption, tracking grid mix composition, timestamping data, and transmitting information. This consolidation of functions into single devices reduces overall system complexity compared to using separate specialized devices for each function.
Solution Approach 2:
The monitoring system is designed to automatically capture, process, and transmit grid mix data without requiring manual intervention. Smart meters self-record consumption data, monitoring devices automatically track renewable energy proportions, and the system autonomously generates carbon footprint calculations, eliminating the need for complex manual data collection and processing infrastructure.
3Measurement precision
If granular time-interval monitoring is used, then measurement precision is improved, but loss of time increases
Solution Approach 1:
The system pre-configures monitoring parameters, data collection intervals, and calculation methodologies before deployment. Smart meters are pre-programmed with measurement protocols, and the system establishes real-time data streams in advance, eliminating the need for gradual system ramp-up or iterative calibration that would consume additional time.
Solution Approach 2:
The system implements continuous uninterrupted monitoring of electricity consumption and grid mix composition. Data collection operates without gaps or interruptions, maintaining constant measurement streams that immediately capture emissions information as it occurs, thereby minimizing any time loss associated with periodic sampling or batch processing.
Data Source
AI summary
Described are various embodiments of system and method for tracking purchased electricity emissions. In one embodiment, a method for determining a carbon footprint of at least one energy consuming process comprises the steps of: surveilling, by a processor, for a designated time interval, an amount of electricity produced by the one or more sources of generation. For each source of generation in said designated time interval, a carbon-footprint of the generated electricity is determined. Electricity consumed by the energy consuming process during said designated time interval can be monitored, in some cases, via one or more local monitoring devices. For each source of generation, a corresponding proportion of the electricity consumed to the energy produced is assigned for the designated time interval. A carbon footprint of the energy consumed for the designated time interval is calculated using the proportion and said carbon footprint of the generated electricity.