JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE) ›› 2017, Vol. 47 ›› Issue (6): 1-6.doi: 10.6040/j.issn.1672-3961.0.2017.541

    Next Articles

Bi-stage optimization method for receiving-end ultra-high voltage network planning under global energy interconnection

LIU Xiaoming1, XU Naiyuan2, YANG Bin1, WEI Xin1, ZHANG Lina1, CAO Yongji3*   

  1. 1. Economic &
    Technology Research Institute, State Grid Shandong Electric Power Company, Jinan 250021, Shandong, China;
    2. State Grid Shandong Electric Power Company, Jinan 250001, Shandong, China;
    3. Collaborative Innovation Center for Global Energy Interconnection(Shandong University), Jinan 250061, Shandong, China
  • Received:2017-10-30 Online:2017-12-20 Published:2017-10-30

Abstract: The ultra-high voltage(UHV)grid serves as a critical support technology of the global energy interconnection, of which network configuration may seriously impact the security and economical efficiency of global energy. Taking into account the layout of UHV receiving point and regulation of receiving-end network structure simultaneously, a bi-stage optimization approach was proposed to deal with the problem of receiving-end UHV network planning. In the first stage, a tri-objective optimization model(TOOM)of the UHV receiving point planning was established to maximize the strength of receiving-end system and the static voltage stability, and minimize the active transmission power loss. Then, the normalization and scalarization methods were implemented to solve the TOOM. In the second stage, the short circuit current level and cost-performance ratio were utilized as indices and the network structure was regulated based on the BPA software to ensure the safe and reliable operation. Shandong power grid was taken as a case study and the results validated the effectiveness of proposed approach.

Key words: receiving-end high voltage network, bi-stage planning, global energy interconnection, cost-performance ratio, scalarizing method, tri-objective optimization, normalization method

CLC Number: 

  • TM734
[1] 刘振亚. 全球能源互联网[M]. 北京: 中国电力出版社, 2015.
[2] 张恒旭, 施啸寒, 刘玉田, 等. 我国西北地区可再生能源基地对全球能源互联网构建的支撑作用[J]. 山东大学学报(工学版), 2016, 46(4): 96-102. ZHANG Hengxu, SHI Xiaohan, LIU Yutian, et al. Support of the renewable energy base in northwest of China on the construction of global energy interconnection[J]. Journal of Shandong University(Engineering Science), 2016, 46(4): 96-102.
[3] 张小平, 李佳宁, 付灏. 全球能源互联网对话工业4.0[J]. 电网技术, 2016, 40(6): 1607-1611. ZHANG Xiaoping, LI Jianing, FU Hao. Global energy interconnection dialogue industry 4.0[J]. Power System Technology, 2016, 40(6): 1607-1611.
[4] 王益民. 全球能源互联网理念及前景展望[J]. 中国电力, 2016, 49(3): 1-5. WANG Yimin. Concept and prospect of global energy interconnection[J]. Electric Power, 2016, 49(3): 1-5.
[5] CAO Y, ZHANG Y, ZHANG H, et al. Probabilistic optimal PV capacity planning for wind farm expansion based on NASA data[J]. IEEE Transactions on Sustainable Energy, 2017, 8(3): 1291-1300.
[6] 刘振亚. 特高压交直流电网[M]. 北京: 中国电力出版社, 2013.
[7] 吴耀文, 马溪原, 方华亮, 等. 大规模风电特高压专用通道落点优选方法[J]. 中国电机工程学报, 2012, 32(1): 9-16. WU Yaowen, MA Xiyuan, FANG Hualiang, et al. Selection method of optimal access point for large scale wind power transmission UHV corridor[J]. Proceedings of the CSEE, 2012, 32(1): 9-16.
[8] 邵瑶, 汤涌, 郭小江, 等. 多直流馈入华东受端电网暂态电压稳定性分析[J]. 电网技术, 2011, 35(12): 50-55. SHAO Yao, TANG Yong, GUO Xiaojiang, et al. Transient voltage stability analysis of east China receiving-end power grid with multi-infeed HVDC transmission lines[J]. Power System Technology, 2011, 35(12): 50-55.
[9] 周勤勇, 刘玉田, 汤涌. 受端电网最大直流受入规模分析方法[J]. 高电压技术, 2015, 41(3): 770-777. ZHOU Qinyong, LIU Yutian, TANG Yong. Analysis method for the maximum HVDCs' capacity to receiving-end power grid[J]. High Voltage Engineering, 2015, 41(3): 770-777.
[10] 杨海涛, 吉平, 刘晋雄, 等. 特高压网架方案功能和可靠性分析[J]. 高电压技术, 2017, 43(3): 1014-1022. YANG Haitao, JI Ping, LIU Jinxiong, et al. Analysis on the function and reliability of UHV grid-frame schemes[J]. High Voltage Engineering, 2017, 43(3): 1014-1022.
[11] LONG R, ZHANG J. Risk assessment method of UHV AC/DC power system under serious disasters[J]. Energies, 2016, 10(1): 13.
[12] WANG B, DONG X, BO Z, et al. RTDS environment development of ultra-high-voltage power system and relay protection test[J]. IEEE Transactions on Power Delivery, 2008, 23(2): 618-623.
[13] TENG Y, LI X, HUANG Q, et al. A novel high-frequency voltage standing-wave ratio-based grounding electrode line fault supervision in ultra-high voltage DC transmission systems[J]. Energies, 2017, 10(3): 309.
[14] YU W, XUE Y, LUO J, et al. An UHV grid security and stability defense system: considering the risk of power system communication[J]. IEEE Transactions on Smart Grid, 2015, 7(1): 491-500.
[15] MIAO Y, CHENG H. An optimal reactive power control strategy for UHVAC/DC hybrid system in east China grid[J]. IEEE Transactions on Smart Grid, 2015, 7(1): 392-399.
[16] 王同文, 许文格, 管霖. 电力网的网架结构优化规划方法[J]. 继电器, 2005, 33(21): 58-64. WANG Tongwen, XU Wenge, GUAN Lin. Method for optimal programming of the electric power structure[J]. Relay, 2005, 33(21): 58-64.
[17] 陆文甜, 林舜江, 刘明波, 等. 含风电场的交直流互联电力系统网省协调有功调度优化方法[J]. 电力系统自动化, 2015, 39(7): 89-96. LU Wentian, LIN Shunjiang, LIU Mingbo, et al. A regional and provincial grid coordination optimization method for active power dispatch in AC/DC interconnected power system with wind power integration[J]. Automation of Electric Power Systems, 2015, 39(7): 89-96.
[18] 熊雄, 叶林, 杨仁刚. 风电功率小波包分解结合储能模糊控制的配电网多目标优化[J]. 电力系统自动化, 2015, 39(15): 68-74. XIONG Xiong, YE Lin, YANG Rengang. Distribution power system multi-objective optimization based on wind power wavelet packet decomposition and storage system fuzzy control[J]. Automation of Electric Power Systems, 2015, 39(15): 68-74.
[19] 刘昇, 徐政. 联于弱交流系统的VSC-HVDC稳定运行区域研究[J]. 中国电机工程学报, 2016, 36(1): 133-144. LIU Sheng, XU Zheng. Study on stable operating region of VSC-HVDC connected to weak AC systems[J]. Proceedings of the CSEE, 2016, 36(1): 133-144.
[20] 刘文颖, 文晶, 谢昶, 等. 考虑风电消纳的电力系统源荷协调多目标优化方法[J]. 中国电机工程学报, 2015, 35(5): 1079-1088. LIU Wenying, WEN Jing, XIE Chang, et al. Multi-objective optimal method considering wind power accommodation based on source-load coordination[J]. Proceedings of the CSEE, 2015, 35(5): 1079-1088.
[21] BOYD S, VANDENBERGHE L. Convex optimization[M]. Cambridge: Cambridge University Press, 2004.
[22] XU X, CAO Y, ZHANG H, et al. A multi-objective optimization approach for corrective switching of transmission systems in emergency scenarios[J]. Energies, 2017, 10(8): 1204.
[1] SHI Fang, ZHANG Hengxu, ZHANG Lei. [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2017, 47(6): 151-156.
[2] ZHANG Hengxu, HAN Linxiao, SHI Fang. Optimal allocation of global energy based on minimum deviation method [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2017, 47(6): 128-133.
[3] LI Haishi, XU Xiangyi, ZHANG Lei. Operating mechanism establishment of the global energy interconnection under “the Belt and Road Initiative” situation [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2017, 47(6): 134-142.
[4] ZHANG Xihua, LU Shanshan, SU Jianjun. Countermeasure and technology patent development of global energy interconnection [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2017, 47(6): 143-150.
[5] ZHANG Hengxu, SHI Xiaohan, LIU Yutian, YANG Dong. Support of the renewable energy base in northwest of China on the construction of global energy interconnection [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2016, 46(4): 96-102.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!