Determination of transmission reliability margin using probabilistic load flow

被引:0
|
作者
Lee, JK [1 ]
Shin, DJ [1 ]
Lee, HS [1 ]
Jung, HS [1 ]
Kim, JO [1 ]
机构
[1] Hanyang Univ, Dept Elect Engn, Seoul 133791, South Korea
来源
PROCEEDINGS OF THE FOURTH IASTED INTERNATIONAL CONFERENCE ON POWER AND ENERGY SYSTEMS | 2004年
关键词
ATC; Monte-Carlo simulation; PLF; TRM;
D O I
暂无
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
According to NERC definition, Available Transfer Capability (ATC) is a measure of the transfer capability remaining in the physical transmission network for the future commercial activity. To calculate ATC, accurate and defensible TTC, CBM and TRM should be calculated in advance. This paper proposes a method to quantify time varying Transmission Reliability Margin (TRM) based on probabilistic load flow (PLF) using the method of moments. The uncertainties of power system and market, such as generation output, bus voltages, line outages, line flow and cancellation of power delivery contracts are considered as time varying complex random variables (CRV) in the PLF process. As a result of PLF analysis, Probability Density Function (PDF) of line flow and bus voltage at the transfer interface are acquired, and TRM with the desired probabilistic margin is calculated based on these PDFs. One distinguishing feature of the proposed method is that the TTC and TRM can be computed as a function of a specified probability margin. Suggested TRM quantification method is compared with the results with Monte-Carlo simulation and verified using 24 bus MRTS. The proposed method based on PLF shows efficiency and flexibility for the quantification of TRM.
引用
收藏
页码:350 / 355
页数:6
相关论文
共 50 条
  • [1] The calculation of Transfer Reliability Margin based on the method of probabilistic load flow
    Dong, Lei
    Li, Saifeng
    Yang, Yihan
    Bao, Hai
    2010 ASIA-PACIFIC POWER AND ENERGY ENGINEERING CONFERENCE (APPEEC), 2010,
  • [2] Transmission Reliability Margin Calculation by Modified DC Load Flow Method
    Nadia, Awatif
    Chowdhury, Abdul Hasib
    2019 5TH INTERNATIONAL CONFERENCE ON ADVANCES IN ELECTRICAL ENGINEERING (ICAEE), 2019, : 246 - 250
  • [3] Efficient transmission system probabilistic three-phase load flow
    Gupta, Neeraj
    2022 IEEE INTERNATIONAL CONFERENCE ON POWER ELECTRONICS, DRIVES AND ENERGY SYSTEMS, PEDES, 2022,
  • [4] Security assessment for bus voltages using Probabilistic load flow
    Kim, TK
    Choo, JB
    Lee, SH
    Kim, JO
    Kim, KH
    2004 INTERNATIONAL CONFERENCE ON PROBABILISTIC METHODS APPLIED TO POWER SYSTEMS, 2004, : 888 - 893
  • [5] Risk Assessment for the Amount of Transmission System Usage Penalties via Probabilistic Load Flow
    Milhorance, Andre
    Leite da Silva, Armando M.
    Telles, Erica
    Street, Alexandre
    2020 INTERNATIONAL CONFERENCE ON PROBABILISTIC METHODS APPLIED TO POWER SYSTEMS (PMAPS), 2020,
  • [6] Probabilistic Reliability Analysis in the Norwegian Transmission System
    Bruvik, Katrine
    Hytten, Lars Martin
    2020 INTERNATIONAL CONFERENCE ON PROBABILISTIC METHODS APPLIED TO POWER SYSTEMS (PMAPS), 2020,
  • [7] Probabilistic load flow computation using saddle-point approximation
    Kenari, Meghdad Tourandaz
    Sepasian, Mohammad Sadegh
    Nazar, Mehrdad Setayesh
    COMPEL-THE INTERNATIONAL JOURNAL FOR COMPUTATION AND MATHEMATICS IN ELECTRICAL AND ELECTRONIC ENGINEERING, 2017, 36 (01) : 48 - 61
  • [8] Probabilistic load flow using improved three point estimate method
    Che, Yulong
    Wang, Xiaoru
    Lv, Xiaoqin
    Hu, Yi
    INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2020, 117 (117)
  • [9] Modeling of Correlated Photovoltaic Generations and Load Demands in Probabilistic Load Flow
    Prusty, B. Rajanarayan
    Jena, Debashisha
    2015 ANNUAL IEEE INDIA CONFERENCE (INDICON), 2015,
  • [10] Probabilistic Load Flow of Power System With Traction Power Load of Electrified Railways
    Chen W.
    Jiang T.
    Dai C.
    Yuan S.
    Zhongguo Dianji Gongcheng Xuebao/Proceedings of the Chinese Society of Electrical Engineering, 2019, 39 (23): : 6899 - 6907