Bi-level optimization model of inter-regional power dispatch based on regional electricity price

被引：0
|
作者：
Zhang L. [1 ]
Wang X. [1 ]
Wang J. [1 ]
Zheng Y. [1 ]
Ma Q. [2 ]
Wang Z. [2 ]
机构：
[1] School of Electrical Engineering, Xi’an Jiaotong University, Xi’an
[2] Power Dispatching Control Center of China Southern Power Grid, Guangzhou
来源：
Dianli Zidonghua Shebei/Electric Power Automation Equipment | 2023年 / 43卷 / 08期
关键词：
bi-level optimization; chance constraint; equivalent generation cost curve; inter-regional power dispatch; KKT condition;
D O I：
10.16081/j.epae.202301025
中图分类号：
学科分类号：
摘要：
In order to fully use the inter-regional dispatch resource，a bi-level optimization model of inter-regional power dispatch based on regional electricity price is proposed. The equivalent generation cost curve is adopted to model the output of coal-fired units within the regions，and the chance constraint method based on integer programming is adopted to model the output of wind power and photovoltaic. A bi-level optimization model suitable for hierarchical dispatch mode is established. As the superior dispatch organization，the upper level model takes the inter-regional transmission power as the decision variables，and takes the maximum value of inter-regional transmission electricity as the goal. The lower level model realizes the economic dispatch within the regions. The bi-level model is transformed into a single-level model for solution according to Karush-Kuhn-Tucker（KKT） condition. The example results verify the effectiveness of the proposed model，which maintains a certain electricity price difference between the power sending region and power receiving region，and alleviates the power supply and demand contradiction in the power receiving region by transmitting a small amount of electricity. © 2023 Electric Power Automation Equipment Press. All rights reserved.
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页码：195 / 201
页数：6
相关论文
共 20 条
  • [1] Dan XU, GE Rui, CAI Zhi, Et al., Optimization and adjustment method for intraday generation scheduling of regional power grid considering large-scale power loss［J］, Automation of Electric Power Systems, 41, 7, pp. 68-73, (2017)
  • [2] YAN Sizhe, WANG Weiqing, LI Xiaozhu, Et al., Cross-regional flexible robust optimal scheduling in dynamic economic environment with joint frequency regulation of energy storage and units［J］, Automation of Electric Power Systems, 46, 9, pp. 61-70, (2022)
  • [3] LI Yunlong, LI Zhigang, ZHENG Jiehui, Distributionally robust economic dispatch of multi-regional power grid considering uncertainty and correlation of wind power［J］, Electric Power Automation Equipment, 41, 8, pp. 97-104, (2021)
  • [4] XU Fan, DING Qia, HAN Hongwei, Et al., Power optimization model and analysis of HVDC tie-line for promoting integration of inter-regional renewable energy accommodation［J］, Automation of Electric Power Systems, 41, 18, pp. 152-159, (2017)
  • [5] XU Dan, WANG Bin, ZHANG Jiali, Et al., Integrated transmission scheduling model for wind-photovoltaic-thermal power by ultra-high voltage direct current system［J］, Automation of Electric Power Systems, 40, 6, pp. 25-29, (2016)
  • [6] LIU Dewei, HUANG Yuehui, WANG Weisheng, Et al., Analysis on provincial system available capability of accommodating wind power considering peak load dispatch and transmission constraints［J］, Automation of Electric Power Systems, 35, 22, pp. 77-81, (2011)
  • [7] LIU Shuyan, LIAO Yang, CHAI Qingxuan, Et al., Coordinated abandoned wind accommodation analysis of multi-area interconnected combined heat and power system considering exchanging power cost［J］, Electric Power Automation Equipment, 42, 4, pp. 48-54, (2022)
  • [8] Decentralized multiarea robust generation unit and tie-line scheduling under wind power uncertainty［J］, IEEE Transactions on Sustainable Energy, 6, 4, pp. 1377-1388, (2015)
  • [9] QIN J H, Et al., A Newton method-based distributed algorithm for multi-area economic dispatch ［J］, IEEE Transactions on Power Systems, 35, 2, pp. 986-996, (2020)
  • [10] Decentralized multi-area economic dispatch via dynamic multiplier-based Lagrangian relaxation［J］, IEEE Transactions on Power Systems, 30, 6, pp. 3225-3233, (2015)
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