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Work item:
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L.TR_GHG_DR
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Subject/title:
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Mechanism and framework of power grid demand response based on GHG emission factor
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Status:
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Under study
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Approval process:
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AAP
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Type of work item:
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Recommendation
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Version:
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New
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Equivalent number:
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-
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Timing:
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2026 (Medium priority)
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Liaison:
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ITU-T SG20
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Supporting members:
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State Grid Corporation of China, Tsinghua University (China), China Telecommunications Corporation
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Summary:
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This Technical Report focuses on developing a mechanism for demand response based on GHG emission factor, it also shows the potential realization paths for demand response based on GHG emission factor. Some use cases is given by utilizing virtual power plant with digital twin technology to achieve this mechanism.
The objectives of proposed mechanism are to guide power users (e.g., data centers, telecom base stations) to "use more low-carbon electricity and less high-carbon electricity" by dynamic GHG emission factor. This mechanism links carbon emission data with time-of-use (TOU) pricing in an electricity-carbon joint market, enabling users to adjust consumption patterns based on real-time carbon intensity. Users can shift loads from high-emission periods/regions to low-emission ones, with certified emission reductions converted into tradable carbon credits for economic incentives.
The mechanism is mainly divided into two parts:
Part 1: Dynamic GHG emission Factor-Driven Demand Response
1.Data Collection: Calculate users' dynamic GHG emission factors based on real-time grid GHG emission data and power flow information.
2.Strategy Optimization: Users adjust their power consumption plans by integrating price signals from the electricity-carbon market with their own emission reduction targets.
3.Assess and settle carbon reductions: Calculate emission reductions and generate carbon credits based on actual power consumption curves and GHG emission factors.
Part 2: Electricity-Carbon Market Value Conversion Mechanism
1.Carbon Price-Linked TOU Pricing: Implement preferential electricity prices during low-carbon periods to guide load shifting toward peak green power hours.
2.Carbon Credit Trading: Users convert emission reductions into tradable credits, which can be sold for profit or used to offset their own carbon quotas.
3.Two-Way Reward-Penalty Mechanism: Subsidies are provided for users who exceed emission reduction targets, while price penalties apply to non-compliant high emitters.
The two parts form a closed loop of "signal guidance - behavioural response - benefit feedback", driving users to shift from passive energy saving to active carbon management.
It also describes the potential realization paths for demand response based on GHG emission factor. Those Technologies should aggregate distributed resources (e.g., renewable energy, controllable loads) and achieve real-time monitoring of power system carbon dynamics. Some key technical components include defining dynamic carbon metrics, designing dual-value (energy and environmental) pricing signals, and establishing user-level carbon reduction evaluation methods are given.
At last, use cases of demand response based on GHG emission factor utilizing virtual power plant with digital twin technology is described. By utilizing this mechanism in Wuhan (laser enterprise) and Beijing (108 companies) demonstrate average 1.5% carbon reductions and also get rewarding from electricity-carbon integrated market.
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Comment:
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-
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Reference(s):
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Historic references:
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Contact(s):
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First registration in the WP:
2025-06-25 13:36:10
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Last update:
2025-07-02 10:29:48
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