Multi-market Demand Response Bidding Strategy for Load Aggregators Based on Bilateral Time Granularity Matching Framework

Simian Pang; Yongbiao Yang; Qingshan Xu; Jiao Du; Jiancheng Yu; Chao Pang

doi:10.35833/MPCE.2025.000812

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Multi-market Demand Response Bidding Strategy for Load Aggregators Based on Bilateral Time Granularity Matching Framework

Original Paper | 更新时间：2026-09-28

- Multi-market Demand Response Bidding Strategy for Load Aggregators Based on Bilateral Time Granularity Matching Framework
- Multi-market Demand Response Bidding Strategy for Load Aggregators Based on Bilateral Time Granularity Matching Framework
- MPCE 2026年14卷第5期页码：1882-1895
- 作者机构：
  
  1.School of Electrical Engineering, Southeast University, Nanjing, China
  2.State Grid Tianjin Electric Power Company, Tianjin, China
- 作者简介：
  
  Simian Pang received the B.S. and M.S. degrees from Sichuan University, Chengdu, China, in 2020 and 2023, respectively. He is currently pursuing the Ph.D. degree with the School of Electrical Engineering, Southeast University, Nanjing, China. His research interests include demand-side management, distribution network optimization, and flexible load dispatching. Email:230238821@seu.edu.cn
  Yongbiao Yang received the B.S. degree from Southwest Jiaotong University, Chengdu, China, in 2001, and the M.S. degree from Nanjing University of Science and Technology, Nanjing, China, in 2013. He is currently working as a Senior Engineer in School of Electrical Engineering, Southeast University, Nanjing, China. His research interests include reliability analysis, demand response, and integrated energy system. Email:103200017@seu.edu.cn
  Qingshan Xu received the B.S. degree from Southeast University, Nanjing, China, in 2000, the M.S. degree from Hohai University, Nanjing, China, in 2003, and the Ph.D. degree from Southeast University in 2006. He is currently working as a Professor in School of Electrical Engineering, Southeast University. His research interests include renewable energy and power system control. Email:xuqingshan@seu.edu.cn
  Jiao Du received the B.S. and M.S. degrees from Southeast University, Nanjing, China, in 2007 and 2010, respectively, and the M.S. degree from the University of Hong Kong, Hong Kong, China, in 2021. She is currently working in Southeast University. Her research interests include load resource scheduling and supply-demand interaction, integrated energy system, and smart power distribution and consumption technology. Email:2783 52439@qq.com
  Jiancheng Yu received the M.S. and Ph.D. degrees in electrical engineering from Tianjin University, Tianjin, China, in 2003 and 2006, respectively. He is the Senior Engineer (Professor level) of State Grid Tianjin Electric Power Company, Tianjin, China. His research interests include distribution network planning, distributed power supply, and smart power distribution and consumption. Email:jiancheng.yu@tj.sgcc.com.cn
  Chao Pang received the B.S. and M.S. degrees from the School of Electrical Engineering, Southwest Jiaotong University, Chengdu, China, in 2018 and 2021, respectively. His research interest includes protection of high-voltage direct current transmission systems. Email:chao.pang@tj.sgcc.com.cn
- 基金信息：
  
  Smart Grid-National Science and Technology Major Project(2024ZD0800800);Science and Technology Project of State Grid Corporation of China “Low-carbon and Reliable Urban Power Distribution System Demonstration Project”(SGTJDK00DWJS2400298)
- DOI：10.35833/MPCE.2025.000812
  中图分类号：
- 收稿：2025-08-31，
  
  修回：2025-12-06，
  
  录用：2026-02-05，
  
  网络首发：2026-04-01，
  
  纸质出版：2026-09-15
- 稿件说明：
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Simian Pang, Yongbiao Yang, Qingshan Xu, 等. Multi-market Demand Response Bidding Strategy for Load Aggregators Based on Bilateral Time Granularity Matching Framework[J]. MPCE, 2026,14(5):1882-1895.

Pang Simian,Yang Yongbiao,Xu Qingshan,et al.Multi-market Demand Response Bidding Strategy for Load Aggregators Based on Bilateral Time Granularity Matching Framework[J].Journal of Modern Power Systems and Clean Energy,2026,14(05):1882-1895.
Simian Pang, Yongbiao Yang, Qingshan Xu, 等. Multi-market Demand Response Bidding Strategy for Load Aggregators Based on Bilateral Time Granularity Matching Framework[J]. MPCE, 2026,14(5):1882-1895. DOI： 10.35833/MPCE.2025.000812.

Pang Simian,Yang Yongbiao,Xu Qingshan,et al.Multi-market Demand Response Bidding Strategy for Load Aggregators Based on Bilateral Time Granularity Matching Framework[J].Journal of Modern Power Systems and Clean Energy,2026,14(05):1882-1895. DOI： 10.35833/MPCE.2025.000812.

摘要

Abstract

Power systems with renewable energy penetration increasingly rely on flexible loads to provide ancillary services

including emergency DR renewable energy consumption

peak shaving

and valley filling. However

the demand response (DR) characteristics of diversified loads such as long DR delay time and ramp-up time do not match the high-resolution bidding and fast-response requirements of ancillary services. To address this challenge

this paper proposes a multi-market DR bidding strategy for load aggregators (LAs). First

the specific bidding resolution and response frequency rules of emergency DR

renewable energy consumption

peak shaving

and valley filling are analyzed

leading to the establishment of a market-side time granularity model. Meanwhile

the DR characteristics of flexible loads

including DR delay time

ramp-up time

and duration

are reformulated into a load-side time granularity model based on DR deviation penalty rules. A bilateral time granularity matching framework is then constructed to enable coarse-grained loads to participate in fine-grained markets through coordinated aggregation. To enable the distributed optimization of DR bidding plans and load response schedules under the management of LAs

a multi-market DR bidding strategy based on bilateral time granularity matching framework is developed. Case studies demonstrate that the proposed strategy effectively unlocks the time flexibility of diversified loads

allowing them to participate in multiple markets and maximize economic benefits.

关键词

Keywords

references

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