JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE) ›› 2017, Vol. 47 ›› Issue (6): 26-31.doi: 10.6040/j.issn.1672-3961.0.2017.538

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Interval optimization method for reference network adaptable to the uncertainties of power sources and electric loads

SUN Donglei1, LI Shan1, LI Xueliang1, HAN Xueshan2,3, LI Wenbo4, YANG Si1   

  1. 1. Economic &
    Technology Research Institute, State Grid Shandong Electric Power Company, Jinan 250021, Shandong, China;
    2. Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education(Shandong University), Jinan 250061, Shandong, China;
    3. Collaborative Innovation Center for Global Energy Internet(Shandong), Jinan 250061, Shandong, China;
    4. State Grid Shandong Electric Power Research Institute, Jinan 250002, Shandong, China
  • Received:2017-09-12 Online:2017-12-20 Published:2017-09-12

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Abstract: Aimed at the shortage of the existing reference network models that rarely take the uncertainties of power sources and electric loads as well as the operation strategies of responding uncertainties into consideration, an interval optimization method for reference network adaptable to the uncertainties of power sources and electric loads was proposed to provide theoretical guidance for flexible electric network planning. Based on the forecasted interval level of uncertain power sources and electric loads in the planning period and candidate schemes in network planning strategy, a novel interval optimization model for reference network was built to minimize the total generation cost, reserve allocation cost and transmission investment cost, in which the security region constraints under all operating modes should be respected. The solution method was given for the proposed model to get the optimal planning scheme for electric network. Finally, case studies were conducted to demonstrate the effectiveness of the proposed method.

Key words: reference network, interval optimization, flexible electric network planning, power grid evaluation, electric network operation strategy

CLC Number: 

  • TM315
[1] 刘振亚. 全球能源互联网[M]. 北京: 中国电力出版社, 2015.
[2] ELA E, O'MALLEY M. Studying the variability and uncertainty impacts of variable generation at multiple timescales[J]. IEEE Transactions on Power Systems, 2012, 27(3): 1324-1333.
[3] 刘晓明, 牛新生, 张怡, 等. 基于 NASA 观测数据的风电出力时空分布及波动特性分析[J]. 山东大学学报(工学版), 2016, 46(4): 111-116. LIU Xiaoming, NIU Xinsheng, ZHANG Yi, et al. Analysis of spatial and temporal distribution of wind power output and variation characteristics based on NASA observation data [J]. Journal of Shandong University(Engineering Science), 2016, 46(4): 111-116.
[4] 薛禹胜, 雷兴, 薛峰, 等. 关于风电不确定性对电力系统影响的评述[J].中国电机工程学报, 2014, 34(29): 5029-5040. XUE Yusheng, LEI Xing, XUE Feng, et al. A review on impacts of wind power uncertainties on power systems[J]. Proceedings of the CSEE, 2014, 34(29): 5029-5040.
[5] 鲁宗相, 李海波, 乔颖. 含高比例可再生能源电力系统灵活性规划及挑战[J]. 电力系统自动化, 2016, 40(13): 147-158. LU Zongxiang, LI Haibo, QIAO Ying. Power system flexibility planning and challenges considering high proportion of renewable energy[J]. Automation of Electric Power Systems, 2016, 40(13):147-158.
[6] 李山. 参考电网建模及优化方法研究[D]. 济南: 山东大学, 2017. LI Shan. Research on modeling and optimization methods of reference network[D]. Jinan: Shandong University, 2017.
[7] MINOIA A. Reference transmission network: a game theory approach[J]. IEEE Transactions on Power Systems, 2006, 21(1): 249-259.
[8] PADHY N P, ROHIT B, MAYANK N. Smart reference networks[C] //2011 IEEE Power and Energy Society General Meeting. Detroit, USA: IEEE Press, 2011.
[9] CALIBJO C C, ALLAN C N. Reference grid performance assessment model for transmission company regulation[C] //IEEE Conference on Power & Energy(IPEC). Ho Chi Minh City, Vietnam: IEEE Press, 2012.
[10] 徐伟, 鲍颜红, 周海锋, 等. 基于阻塞分析的输电线路动态增容[J]. 电力系统保护与控制, 2016, 44(6): 15-22. XU Wei, BAO Yanhong, ZHOU Haifeng, et al. Transmission line dynamic capacity-increase based on congestion analysis[J]. Power System Protection and Control, 2016, 44(6): 15-22.
[11] WANG Y, XIA Q, KANG C. Unit commitment with volatile node injections by using interval optimization[J]. IEEE Transactions on Power Systems, 2011, 26(3): 1705-1713.
[12] ZHAO J, ZHENG T, LITVINOV E. Variable resource dispatch through do-not-exceed limit[J]. IEEE Transactions on Power Systems, 2015, 30(2): 820-828.
[13] 杨明, 程凤璐, 韩学山. 电力系统实时调度的有效静态安全域法[J]. 中国电机工程学报, 2015, 35(6): 1353-1362. YANG Ming, CHENG Fenglu, HAN Xueshan. Real-time dispatch based on effective steady-state security regions of power system[J]. Proceedings of the CSEE, 2015, 35(6): 1353-1362.
[14] JABR R A, KARAKI S, KORBANE J A. Robust multi-period OPF with storage and renewables[J]. IEEE Transactions on Power Systems, 2015, 30(5): 2790-2799.
[15] 孙东磊. 电力系统源、网协同调度的理论研究[D]. 济南: 山东大学, 2016. SUN Donglei. Theoretical studies on synergistic dispatch of power source and electric network in power system[D]. Jinan: Shandong University, 2016.
[16] KWON J, HEDMAN K W. Transmission expansion planning model considering conductor thermal dynamics and high temperature low sag conductors[J]. IET Generation Transmission & Distribution, 2015, 9(15):2311-2318.
[17] AMIN K, SHAHIDEHPOUR M, KAMALINIA S. Transmission switching in expansion planning[J]. IEEE Transactions on Power Systems, 2010, 25(3): 1722-1733.
[18] VILLUMSEN A, CHRISTOFFER J, BRONMO G, et al. Line capacity expansion and transmission switching in power systems with large-scale wind power[J]. IEEE Transactions on Power Systems, 2013, 28(2): 731-739.
[19] 孙东磊, 韩学山, 张波. 电力系统运行协同的区间有功优化潮流[J]. 电力自动化设备, 2016, 36(1): 97-104. SUN Donglei, HAN Xueshan, ZHANG Bo. Synergetic interval optimal active power flow of power system operation [J]. Electric Power Automation Equipment, 2016, 36(1): 97-104.
[20] ZIMMERMAN R D, MURILLO-SÁNCHEZ C E, GAN D D. MATPOWER: a MATLAB power system simulation package[EB/OL]. 1997[2017-06-05]. http://www.pserc.cornell. edu/matpower/.
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