Carbon-Aware Bi-Level Coordination of Electric Vehicles and Distribution Networks Via Dynamic Electricity-Carbon Signals

This paper addresses the coordinated dispatch challenge of large-scale Electric Vehicles (EVs) in Active Distribution Networks (ADNs) through a bi-level low-carbon optimization framework with electro-carbon demand response (ECDR). First, EV aggregators’ schedulable capacity is characterized via Monte Carlo simulation and Minkowski summation. Second, a dynamic carbon intensity model for EV consumption is established using carbon emission flow theory, coupled with an integrated electricity-carbon market benefit model. The electricity market operator minimizes total energy costs through market clearing while announcing dynamic carbon intensities. EV aggregators then optimize bidding strategies to maximize benefits based on market outcomes and carbon factors. Case studies validate the framework’s economic and environmental effectiveness.

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Publication Details

Published
2025-06-20
DOI
https://doi.org/10.1109/icetac65964.2025.11144158
Primary Topic
Blockchain Technology Applications and Security
Type
article
Field-Weighted Citation Impact
0.00

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article

Carbon-Aware Bi-Level Coordination of Electric Vehicles and Distribution Networks Via Dynamic Electricity-Carbon Signals

Peilin He, Houpeng Hu, Xiaoming Lin, Zerui Chen et al.
Blockchain Technology Applications and Security
article

Carbon-Aware Bi-Level Coordination of Electric Vehicles and Distribution Networks Via Dynamic Electricity-Carbon Signals

Peilin He, Houpeng Hu, Xiaoming Lin, Zerui Chen, Jianlin Tang, Bin Qian, Mi Zhou, Yanhong Xiao
article en

Abstract

This paper addresses the coordinated dispatch challenge of large-scale Electric Vehicles (EVs) in Active Distribution Networks (ADNs) through a bi-level low-carbon optimization framework with electro-carbon demand response (ECDR). First, EV aggregators’ schedulable capacity is characterized via Monte Carlo simulation and Minkowski summation. Second, a dynamic carbon intensity model for EV consumption is established using carbon emission flow theory, coupled with an integrated electricity-carbon market benefit model. The electricity market operator minimizes total energy costs through market clearing while announcing dynamic carbon intensities. EV aggregators then optimize bidding strategies to maximize benefits based on market outcomes and carbon factors. Case studies validate the framework’s economic and environmental effectiveness.

Guizhou Electric Power Design and Research Institute (CN), China National Electric Apparatus Research Institute (China) (CN)
China Southern Power Grid
Openalex Percentile: Top 65%
Blockchain Technology Applications and Security
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