The Design of the Model of Wind Power Integration Based on Thermal Power Peak-shaving

被引:0
|
作者
Yu, Zhao [1 ]
Li, Dongxue [2 ]
Lin, Jia [1 ]
Jiang, Tong [1 ]
Yu, Dayong [2 ]
机构
[1] North China Elect Power Univ, Power Grid Res Inst, Beijing, Peoples R China
[2] State Power Econ Res Inst, Liaoning, Peoples R China
关键词
wind power; wind power integration model; peak-shaving; social benefits; economic benefits;
D O I
暂无
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
With the country promoting the power from new energy sources, wind power was attached with great importance gradually. However, there is an existing major problem in the field of wind power, that it is the lack of peak-shaving capacity, which leads the capacity of wind power integration to be limited. For solving the problem of the lack of peak-shaving capacity, the models of "equivalent load" and "equivalent power injection" and the wind power integration model based on thermal power peak-shaving capacity is built in this paper, which takes controlling the capacity of wind power integration reasonably as target. The model can forecast the maximum power of wind power integrated in the power grid in real time. The reasonability of the model is verified by an actual example. Furthermore, for obtaining more social benefits and economic benefits, this paper analyzes wind power control strategies in both cases of conventional peak-shaving and deep peak-shaving. Finally, the paper gets the following conclusion. In the case of conventional peak-shaving, wind power should be controlled reasonably according to the peak-shaving capacity of thermal power. In the case of deep peak-shaving, peak-shaving cost should be increased for eliminating the crowding-out effect.
引用
收藏
页码:1005 / 1008
页数:4
相关论文
共 50 条
  • [1] MANEUVERABILITY OF PEAK-SHAVING POWER-STATIONS
    SCHRAMM, G
    ENERGIETECHNIK, 1978, 28 (04): : 145 - 149
  • [2] Coordinated dispatching method of unconventional peak-shaving and abandoned wind for power grid
    Ge, Weichun
    Taiyangneng Xuebao/Acta Energiae Solaris Sinica, 2019, 40 (11): : 3324 - 3330
  • [3] Multi-Power Joint Peak-Shaving Optimization for Power System Considering Coordinated Dispatching of Nuclear Power and Wind Power
    Liu, Qi
    Zhao, Jie
    Shao, Youguo
    Wen, Libin
    Wu, Jianxu
    Liu, Dichen
    Ma, Yuhui
    SUSTAINABILITY, 2019, 11 (17)
  • [4] A New Peak-Shaving Model Based on Mixed Integer Linear Programming with Variable Peak-Shaving Order
    Cheng, Xianliang
    Feng, Suzhen
    Huang, Yanxuan
    Wang, Jinwen
    ENERGIES, 2021, 14 (04)
  • [5] PEAK-SHAVING RATIO ANALYSIS OF THE NATURAL GAS COMBINED HEAT AND POWER PLANT WITH DISTRIBUTED PEAK-SHAVING HEAT PUMPS
    Zhao, Xiling
    Wang, Xiaoyin
    Sun, Tao
    PROCEEDINGS OF THE ASME 11TH INTERNATIONAL CONFERENCE ON ENERGY SUSTAINABILITY, 2017, 2017,
  • [6] Power systems' optimal peak-shaving applying secondary storage
    Levron, Yoash
    Shmilovitz, Doron
    ELECTRIC POWER SYSTEMS RESEARCH, 2012, 89 : 80 - 84
  • [7] Optimal scheduling for unit commitment considering wind power consumption and natural gas peak-shaving
    Liu, Yawei
    Du, Qinjun
    Wang, Chen
    Ma, Bingtu
    Wu, Yutong
    Liu, Decai
    JOURNAL OF COMPUTATIONAL METHODS IN SCIENCES AND ENGINEERING, 2024, 24 (4-5) : 2175 - 2185
  • [8] Optimization model of combined peak shaving of virtual power grid and thermal power based on power IoT
    Wang, Yong
    Wang, Peng
    Guo, Mengxin
    Lei, Zhenjiang
    Luo, Xiyun
    ELECTRICAL ENGINEERING, 2025, 107 (01) : 1225 - 1233
  • [9] A Real-Time Power Distribution based on Load/Generation Forecasting for Peak-Shaving
    Nishihara, Hide
    Taniguchi, Ittetsu
    Kato, Shinya
    Fukui, Masahiro
    2013 IEEE 11TH INTERNATIONAL NEW CIRCUITS AND SYSTEMS CONFERENCE (NEWCAS), 2013,
  • [10] Peak-shaving Method of Hydro-wind Power Complementary System Based on C-vine Copula Theory
    Zhang B.
    Shen J.
    Cheng C.
    Jiang Y.
    Zhang C.
    Zhongguo Dianji Gongcheng Xuebao/Proceedings of the Chinese Society of Electrical Engineering, 2022, 42 (15): : 5523 - 5534