Coordinated scheduling strategy for power grid's new energy generation output and load regulation characteristics

被引:0
|
作者
Zhang, Shaodong [1 ]
Teng, Yun [1 ]
Li, Zifeng [1 ]
Li, Ziwei [1 ]
机构
[1] Shenyang Univ Technol, Shenyang 110870, Liaoning, Peoples R China
关键词
power grid; distributing electricity; power system; coordinated scheduling strategy;
D O I
10.1145/3674225.3674328
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
With the increasing penetration of distributed energy resources, the existing hierarchical scheduling operation mode of networks for transmitting and distributing electricity faces challenges in achieving global optimization. This paper proposes a coordinated scheduling strategy for power grid's new energy generation output and load regulation characteristics. Firstly, the coordination relationship of networks for transmitting and distributing electricity is analyzed, and a demand response scheduling framework and a demand response model for transmission and distribution coordination are constructed. Secondly, considering the risks caused by fluctuations in the system's operation, an uncertainty model for renewable energy and demand-side response is established. Then, the uncertainty model is combined with a robust model to build a robust optimization scheduling model for coordinated distribution of distributed energy resources and demand-side response. A simulation model built upon operational data of a specific transmission and distribution system is used to validate the efficacy of the proposed optimization scheduling approach. This strategy enables interactive coordination between electricity transmission and distribution grids, optimizing operating costs and operating risks synergistically.
引用
收藏
页码:571 / 575
页数:5
相关论文
共 50 条
  • [41] Optimal energy scheduling strategy for multi-energy generation grid using multi-agent systems
    Khan, Muhammad Waseem
    Wang, Jie
    Xiong, Linyun
    [J]. INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2021, 124
  • [42] Heterogeneous Energy Complementary Power Generation Dispatching Based on Output-load Matching
    Zhang, Xinshuo
    Chen, Shijun
    Zeng, Hong
    Han, Xiaoyan
    Ma, Guangwen
    [J]. Dianwang Jishu/Power System Technology, 2020, 44 (09): : 3314 - 3320
  • [44] Flexibility model of integrated energy system for peak load regulation demand of power grid
    Li, Shiyan
    Tang, Hao
    Fang, Daohong
    [J]. 2022 9TH INTERNATIONAL FORUM ON ELECTRICAL ENGINEERING AND AUTOMATION, IFEEA, 2022, : 325 - 331
  • [45] Coordinated Frequency Regulation Strategy of Wind, Diesel and Load for Microgrid with High-penetration Renewable Energy
    高渗透率可再生能源微电网的风柴荷协调调频策略
    [J]. Zhao, Yao (nihaozhaoyao@163.com), 2018, Automation of Electric Power Systems Press (42):
  • [46] A swarm intelligence and deep learning strategy for wind power and energy storage scheduling in smart grid
    Geng, Lin
    Zhang, Lei
    Niu, Fangming
    Li, Yang
    Liu, Feng
    [J]. International Journal of Intelligent Networks, 2024, 5 : 302 - 314
  • [47] Coordinated control strategy of DC microgrid with hybrid energy storage system to smooth power output fluctuation
    Wu, Tiezhou
    Ye, Fanchao
    Su, Yuehong
    Wang, Yubo
    Riffat, Saffa
    [J]. INTERNATIONAL JOURNAL OF LOW-CARBON TECHNOLOGIES, 2020, 15 (01) : 46 - 54
  • [48] Power Generation Characteristics of Single Electrode Output Circuit in Electret Energy Harvester
    Bu, L.
    Xu, H. Y.
    Xu, B. J.
    Song, L.
    [J]. 14TH INTERNATIONAL CONFERENCE ON MICRO AND NANOTECHNOLOGY FOR POWER GENERATION AND ENERGY CONVERSION APPLICATIONS (POWERMEMS 2014), 2014, 557
  • [49] Research on wind-storage coordinated frequency regulation strategy of high permeability wind power connected to regional power grid
    wen, Chunxue
    Mo, Jiaxing
    Li, Jianlin
    Zhou, Jinghua
    Wang, Peng
    [J]. ENERGY REPORTS, 2023, 9 : 774 - 785
  • [50] Research on wind-storage coordinated frequency regulation strategy of high permeability wind power connected to regional power grid
    Wen Chunxue
    Mo Jiaxing
    Li Jianlin
    Zhou Jinghua
    Wang Peng
    [J]. ENERGY REPORTS, 2023, 9 : 774 - 785