Energy Storage System Charging via Marginal Emission Factor Data
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Solution Overview
Problem
Utility providers face challenges in managing greenhouse gas emissions due to varying marginal emission factors from different electricity sources, leading to increased emissions during demand shifts, as they rely on sources like natural gas power plants that quickly scale up production, resulting in higher emissions.
Innovation Solution
A system and method that utilize marginal emission factor (MEF) data to monitor and adjust energy storage system operations, such as batteries, to minimize greenhouse gas impacts by charging from lower-emission sources and discharging during higher-emission periods, optimizing energy usage and reducing overall carbon footprint.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If utility providers use natural gas power plants to quickly scale up electricity production during demand shifts, then electricity supply responsiveness is improved, but greenhouse gas emissions increase
Solution Approach 1:
The system performs preliminary actions by charging energy storage systems during low-demand periods when marginal emission factors are low, preparing stored energy to be discharged during high-demand periods. This preemptive energy storage and transfer strategy avoids the need to activate high-emission power plants during demand spikes, thus resolving the contradiction between rapid supply responsiveness and emission reduction
Solution Approach 2:
The patent introduces energy storage systems as an intermediary between electricity generation and consumption. These storage systems decouple the timing of energy production from energy usage, allowing low-emission energy to be stored and used during high-demand periods without requiring high-emission generation sources, thereby mediating the conflict between speed of supply and emission levels
2Object-generated harmful factors
If utility providers rely on steady-output power plants like nuclear plants, then greenhouse gas emissions are reduced, but ability to meet rapidly changing demand is worsened
Solution Approach 1:
The system performs preliminary energy storage during periods when steady-output low-emission power plants are operating, accumulating energy in storage systems before demand increases occur. This allows the system to maintain reliance on steady, low-emission generation while having pre-stored energy available to quickly respond to demand changes, thus preserving both emission reduction and adaptability
Solution Approach 2:
Energy storage systems serve as an intermediary that bridges the gap between steady-output generation and variable demand requirements. The storage systems absorb the variability in demand without requiring the generation sources to vary their output, allowing nuclear and other steady plants to operate at optimal levels while still meeting rapid demand changes through stored energy discharge
3Object-generated harmful factors
If utility customers use energy storage systems to offset greenhouse gas emissions by charging during low-MEF periods and discharging during high-MEF periods, then environmental sustainability is improved, but system complexity increases
Solution Approach 1:
The system implements feedback mechanisms by continuously monitoring marginal emission factor data, battery state of charge, and operational conditions. This feedback enables automated, real-time optimization of charge/discharge decisions based on current emission factors and system state, reducing the complexity burden on customers by providing intelligent, data-driven control that automatically adapts to changing conditions without requiring complex manual management
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach allows utility customers to effectively offset greenhouse gas emissions by aligning energy storage system operations with MEF data, reducing energy consumption and emissions while saving costs, thereby enhancing environmental sustainability.
Implementation Method 1
A system and method that utilize marginal emission factor (MEF) data to monitor and adjust energy storage system operations, such as batteries
Data Source
AI summary
The present solution utilizes marginal emission factor (MEF) data to monitor a greenhouse gas (GHG) impact of an asset, determine a potential to reduce the GHG impact by the asset, and generate operating parameters or settings for a battery at the asset site to reduce the GHG impact through efficient battery operation. For instance, a system can identify a MEF data set of an electricity provider. The system can identify a second data set of measurements of a battery of an asset. The system can determine MEF values corresponding to use of the battery based on the plurality of values and the plurality of measurements over the time period. The system can determine an amount of greenhouse gas or carbon associated with the asset.