基于多粒度柔性负荷特性的多时间尺度混合电价型需求响应

李云鸷; 刘吉臻; 李杰; 胡阳

doi:10.19725/j.cnki.1007-2322.2024.0184

欢迎来到能源电力期刊网！

English Version 期刊登录

您当前的位置：

首页 >

文章列表页 >

基于多粒度柔性负荷特性的多时间尺度混合电价型需求响应

电力市场 | 更新时间：2026-10-19

- 基于多粒度柔性负荷特性的多时间尺度混合电价型需求响应
- Integrated Electricity Tariff-based Demand Response at Multi-time Scales Based on Multi-granularity Flexible Load Features
- 现代电力 2026年43卷第5期页码：906-918
- 作者机构：
  
  华北电力大学控制与计算机工程学院, 北京市昌平区,102206
- 作者简介：
  
  李云鸷(1993)，男，博士研究生，研究方向为综合能源系统建模与调控、电力需求响应，E-mail：liyzhi@ncepu.edu.cn
  刘吉臻(1951)，男，博士，教授，博士生导师，研究方向为电力系统分析、稳定和控制，E-mail：ljz@ncepu.edu.cn
  李杰(2000)，男，硕士研究生，研究方向为综合能源系统优化调度，E-mail：lijie925@ncepu.edu.cn
  胡阳(1986)，男，博士，副教授，通信作者，研究方向为新能源电力系统建模、控制理论研究及应用，E-mail：hooyoung@ncepu.edu.cn
- 基金信息：
  
  国家重点研发计划项目(2021YFE0102400)。
- DOI：10.19725/j.cnki.1007-2322.2024.0184
  中图分类号： 5
- 纸质出版：2026
- 稿件说明：
移动端阅览
李云鸷, 刘吉臻, 李杰, 等. 基于多粒度柔性负荷特性的多时间尺度混合电价型需求响应[J]. 现代电力, 2026,43(5):906-918.

LI Yunzhi, LIU Jizhen, LI Jie, et al. Integrated Electricity Tariff-based Demand Response at Multi-time Scales Based on Multi-granularity Flexible Load Features[J]. 2026, 43(5): 906-918.
李云鸷, 刘吉臻, 李杰, 等. 基于多粒度柔性负荷特性的多时间尺度混合电价型需求响应[J]. 现代电力, 2026,43(5):906-918. DOI： 10.19725/j.cnki.1007-2322.2024.0184.

LI Yunzhi, LIU Jizhen, LI Jie, et al. Integrated Electricity Tariff-based Demand Response at Multi-time Scales Based on Multi-granularity Flexible Load Features[J]. 2026, 43(5): 906-918. DOI： 10.19725/j.cnki.1007-2322.2024.0184.

摘要

随着新型电力系统中可再生能源比例的不断提升，单一电价机制已难以满足系统的灵活性需求。为了充分挖掘电力柔性负荷资源，提出一种多时间尺度混合电价机制。该机制融合容需电价、分时电价、尖峰电价等定价策略，通过电价信号在多时间尺度上引导和鼓励用户调整用电行为。首先，通过时域分析提取用户负荷在不同时间尺度上的变化规律、分布情况及响应特性，评估响应潜力。随后引入多粒度建模思想，根据柔性负荷的容量规模和响应精度划分粒度层级并建立多粒度响应模型。最后，构建季节、日前、日内尺度混合电价优化框架，分别建立两部制电价、阶梯分时电价、尖峰电价和直接控制优化模型，开展电力需求响应。仿真结果表明，该机制能够促进用户负荷在多个时间尺度上转移，在改善负荷曲线、降低用电成本、缓解电网压力等方面表现出显著优势，也为电力市场精细化电价设计提供依据。

Abstract

The increasing proportion of renewable energy in new power systems makes a singular electricity tariff mechanism no longer sufficient to meet the flexibility demands of these systems. A multi-time scale integrated electricity tariff mechanism is proposed to fully exploit the potential of flexible load resources. It combines various pricing strategies

including two-part tariff

time-of-use tariff

and critical peak tariff

aiming to guide and encourage consumers to adjust their electricity consumption behavior across multiple time scales through targeted tariff signals. Firstly

the time-domain analysis is utilized to extract the variation regulation

distribution

response characteristics on the demand side at various time scales

thereby assessing the response potential.Subsequently

the concept of multi-granularity modeling is introduced

which involves dividing the granularity level according to the capacity and response accuracy of flexible loads and establishing a multi-granularity response model. Finally

the optimization models of two-part tariff

stepwise time-of-use tariff

critical peak tariff and direct load control are established respectively

aiming to facilitate demand response within an integrated electricity tariff optimization framework at seasonal

day-ahead

and intraday scales. The simulation results indicate that the proposed mechanism effectively promotes the transfer of load resources across different time scales

thereby offering significant advantages in enhancing power load curve

reducing electricity bills

and alleviating grid pressure. The results also provide a theoretical foundation for the refined pricing design of the electricity market.

关键词

Keywords

references

HUANG Wujing, ZHANG Ning, KANG Chongqing, et al . From demand response to integrated demand response: review and prospect of research and application[J ] . Protection and Control of Modern Power Systems, 2019, 4(2): 1−13.

QI Ning, CHENG Lin, TIAN Liting, et al . Review and prospect of distribution network planning research considering access of flexible load[J ] . Automation of Electric Power Systems, 2020, 44(10): 193−207(in Chinese).

LIU Xinglei, LIU Jun, REN Kezheng, et al . An integrated fuzzy multi-energy transaction evaluation approach for energy internet markets considering judgement credibility and variable ro ugh precision[J ] . Energy, 2022, 261: 125327.

HONG Qiteng, JI Liang, BLAIR S M, et al . A new load shedding scheme with consideration of distributed energy resources’ active power ramping capability[J ] . IEEE Transactions on Power Systems, 2021, 37(1): 81−93.

LI Han, WANG Zhe, HONG Tianzhen, et al . Characterizing patterns and variability of building electric load profiles in time and frequency domains[J ] . Applied Energy, 2021, 291: 116721.

ZHANG Xiaohai, RAMÍREZ-MENDIOLA J L, LI Mingtao, et al . Electricity consumption pattern analysis beyond traditional clustering methods: A novel self-adapting semi-supervised clustering method and application case study[J ] . Applied Energy, 2022, 308: 118335.

KAMINI S, ANOOP S. Behavioural modelling for personal and societal benefits of V2G/V2H integration on EV adoption[J]. Applied Energy, 2022, 319: 119265.

XIA Qing, YANG Zhifang, LAI Xiaowen, et al . Electricity market design based on temporal pricing of renewable capacity[J ] . Power System Technology, 2022, 46(05): 1771−1779(in Chinese).

ZHOU Bin, YA NG Rui, LI Canbing, et al . Multiobjective model of time-of-use and stepwise power tariff for residential consumers in regulated power markets[J ] . IEEE Systems Journal, 2017, 12(3): 2676−2687.

LV Ting, ZHANG Zhi, LU Pengfei, et al . Demand response transaction mechanism for virtual load aggregator considering user credit[J ] . Automation of Electric Power Systems, 2023, 47(19): 44−52(in Chinese).

WANG Lei, HOU Chongqi, YE Bin, et al . Optimal operation analysis of integrated community energy system considering the uncertainty of demand response[J ] . IEEE Transactions on Power Systems, 2021, 36(4): 3681−3691.

LI Hong, LIN Lanxin, ZHAO Xiaojun. Low carbon economic scheduling of electricity-gas-heat integrated energy system based on demand-side user response analysis[J]. Acta Energiae Solaris Sinica, 2023, 44(05): 97−105(in Chinese).

ZHU Lan, TIAN Zeqing, TANG Longjun, et al . Multi-time-scale optimal dispatch of regional integrated energy system considering level of detail direct load control[J ] . Power System Technology, 2021, 45(07): 2763−2774(in Chinese).

ZHAO Yue, CAI Qiuna, WANG Long, et al . Clearing model for ramping ancillary service market considering various demand elasticiti es[J ] . Automation of Electric Power Systems, 2024, 48(05): 48−57(in Chinese).

LUO Zhengyi, PENG Jinqing, YIN Rongxin. Many-objective day-ahead optimal scheduling of residential flexible loads integrated with stochastic occupant behavior models[J]. Applied Energy, 2023, 347: 121348.

NAN Bin, JIANG Chundi, DONG Shufeng, et al . Day-ahead and intra-day coordinated optimal scheduling of integrated energy system considering uncertainties in source and load[J ] . Power System Technology, 2023, 47(09): 3669−3683(in Chinese).

REN Haoshan, GAO Dince, MA Zhenjun, et al . Data-driven surrogate optimization for deploying heterogeneous multi-energy storage to improve demand response performance at building cluster level[J ] . Applied Energy, 2024, 356: 122312.

ZHENG Ruonan, LI Zhihao, TANG Yajie, et al . Incentive demand response model and evaluation considering uncertainty of residential customer participation degree[J ] . Automation of Electric Power Systems, 2022, 46(08): 154−162(in Chinese).

HU Yang, LI Yunzhi, CHEN Longjin. Multi-objective optimization of time-of-use price for tertiary industry based on generalized seasonal multi-model structure[J]. IEEE Access, 2019, 7: 89234−89244.

WEINAN E, ENGQUIST B, HUANG Zhongyi. Heterogeneous multiscale method: A general methodology for multiscale modeling[J]. Physical Review B, 2010, 67(9): 552−555.

ZHENG W , SHEN G Q , WANG H , et al . Decision support for sustainable urban renewal: A multi-scale model[J ] . Land Use Policy, 2017, 69: 361-371.

YANG Shichun, CHENG Hanchao, WANG Mingyue, et al . Multi-scale battery modeling method for fault diagnosis[J ] . Automotive Innovation, 2022, 5: 400−414.

RUAN Wenjun, WANG Beibei, LI Yang, et al . Customer response behavior in time-of-use price[J ] . Power System Technology, 2012, 36(07): 86−93(in Chinese).

浏览量

270

下载量

CSCD

文章被引用时，请邮件提醒。

提交

工具集

关联资源

基于改进多目标灰狼算法和二阶锥规划的主动配电网多时间尺度无功/电压优化控制

考虑风电不确定性的风储电站主动参与电网调压控制策略研究

考虑全寿命周期碳计量和碳交易机制的多目标微电网系统容量优化配置研究

基于改进生成对抗网络生成风光场景的微电网多时间尺度优化调度策略研究

计及运行广义短路比的多时间尺度新能源并网调度计划模型