Dispersed Wind Power Planning Method Considering Network Loss Correction with Cold Weather

被引:0
|
作者
Kou H. [1 ]
Bu T. [1 ]
Mao L. [1 ]
Jiao Y. [2 ]
Liu C. [2 ]
机构
[1] Hulunbeier Power Supply Company, State Grid Inner Mongolia East Power Co., Ltd., Hulunbeier
[2] College of Electrical and Electronic Engineering, North China Electric Power University, Beijing
来源
Energy Eng | 2024年 / 4卷 / 1027-1048期
基金
中国国家自然科学基金;
关键词
Decentralised wind power; manta ray foraging optimisation algorithm; network loss correction; reactive voltage control; siting and capacity determination; two-stage model;
D O I
10.32604/ee.2023.045358
中图分类号
学科分类号
摘要
In order to play a positive role of decentralised wind power on-grid for voltage stability improvement and loss reduction of distribution network, a multi-objective two-stage decentralised wind power planning method is proposed in the paper, which takes into account the network loss correction for the extreme cold region. Firstly, an electro-thermal model is introduced to ref lect the effect of temperature on conductor resistance and to correct the results of active network loss calculation; secondly, a two-stage multi-objective two-stage decentralised wind power siting and capacity allocation and reactive voltage optimisation control model is constructed to take account of the network loss correction, and the multi-objective multi-planning model is established in the first stage to consider the whole-life cycle investment cost of WTGs, the system operating cost and the voltage quality of power supply, and the multi-objective planning model is established in the second stage. planning model, and the second stage further develops the reactive voltage control strategy of WTGs on this basis, and obtains the distribution network loss reduction method based on WTG siting and capacity allocation and reactive power control strategy. Finally, the optimal configuration scheme is solved by the manta ray foraging optimisation (MRFO) algorithm, and the loss of each branch line and bus loss of the distribution network before and after the adoption of this loss reduction method is calculated by taking the IEEE33 distribution system as an example, which verifies the practicability and validity of the proposed method, and provides a reference introduction for decision-making for the distributed energy planning of the distribution network. © 2024, Tech Science Press. All rights reserved.
引用
收藏
页码:1027 / 1048
页数:21
相关论文
共 50 条
  • [31] A Power Network Planning Method with Coal-to-electricity Considering Technical and Economical Adaptability
    An, Jiakun
    Sun, Pengfei
    Han, Jinglin
    Qi, Xiaoguang
    He, Chunguang
    Shao, Hua
    Kang, Wei
    Zhu, Jundong
    2018 2ND IEEE CONFERENCE ON ENERGY INTERNET AND ENERGY SYSTEM INTEGRATION (EI2), 2018,
  • [32] Transmission Expansion Planning Considering Wind Power and Load Uncertainties
    Xie, Yilin
    Xu, Ying
    ENERGIES, 2022, 15 (19)
  • [33] Optimal planning of photovoltaic, wind turbine and battery to mitigate flicker and power loss in distribution network
    Muralikrishnan, G.
    Preetha, K.
    Selvakumaran, S.
    Hariramakrishnan, P.
    JOURNAL OF ENERGY STORAGE, 2025, 116
  • [34] Two-Stage Robust Expansion Planning of Transmission Network Considering Uncertainty of Offshore Wind Power
    Tian, Shuxin
    Han, Xue
    Fu, Yang
    Su, Xiangjing
    Li, Zhenkun
    Shanghai Jiaotong Daxue Xuebao/Journal of Shanghai Jiaotong University, 2024, 58 (09): : 1400 - 1409
  • [35] Source-Network-Storage Joint Planning Considering Energy Storage Systems and Wind Power Integration
    Wu, Xiaosheng
    Jiang, Yuewen
    IEEE ACCESS, 2019, 7 : 137330 - 137343
  • [36] Multiobjective Planning Strategy for a Distribution Network integrated with Wind Power System considering Solid State Transformer
    Gantayet, Amaresh
    Dheer, Dharmendra Kumar
    2021 INTERNATIONAL CONFERENCE ON COMPUTATIONAL PERFORMANCE EVALUATION (COMPE-2021), 2021, : 692 - 697
  • [37] Electricity price driven active distribution network planning considering uncertain wind power and electricity price
    Jiao, P. H.
    Chen, J. J.
    Qi, B. X.
    Zhao, Y. L.
    Peng, K.
    INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2019, 107 : 422 - 437
  • [38] Research on Ultra-short-term Subsection Forecasting Method of Offshore Wind Power Considering Transitional Weather
    Yu G.
    Lu L.
    Tang B.
    Wang S.
    Dong Q.
    Zhongguo Dianji Gongcheng Xuebao/Proceedings of the Chinese Society of Electrical Engineering, 2022, 42 (13): : 4859 - 4870
  • [39] Transmission Grid Planning Considering Operation Efficiency and Wind Curtailment Loss
    Liu Z.
    Yu H.
    Wang S.
    Shi R.
    Wang Z.
    Luo Y.
    Dianwang Jishu/Power System Technology, 2018, 42 (03): : 827 - 834
  • [40] Power network planning for high penetration of dispersed energy resources. Optimal multi-criteria planning method
    Orths, A
    2003 IEEE PES TRANSMISSION AND DISTRIBUTION CONFERENCE & EXPOSITION, VOLS 1-3, CONFERENCE PROCEEDINGS: BLAZING TRAILS IN ENERGY DELIVERY AND SERVICES, 2003, : 393 - 398