张丹宁;徐箭;孙元章;廖思阳;柯德平;

• 1:武汉大学电气与自动化学院

摘要(Abstract)：

随着风电并网规模的日益增加,风电功率的不确定性使得传统确定性备用评估方法已不再适用,系统需要预留合理有效的备用容量以确保系统安全稳定运行。对此,提出备用需求动态评估模型,该模型以风电功率预测和负荷预测的历史数据为基础,把无效向上/向下备用容量、切负荷量和弃风量期望作为评价指标,实现动态评估不同调度时段下受系统不确定性影响的备用需求。而后建立了基于备用需求动态评估的日前优化调度模型,通过4种期望之间的博弈使得系统既不过多预留备用造成浪费,也不因备用预留不足而导致切负荷和弃风。算例分析验证了所提模型的有效性,可为含风电接入系统的运行提供借鉴。

关键词(KeyWords)： 风电;备用需求评估;无效备用容量期望;系统误差

Abstract:

Keywords:

基金项目(Foundation): 国家重点研发计划项目(2016YFB0900100);; 湖北省自然科学基金项目(2017CFB213);; 湖北省杰出青年基金项目(2018CFA080)~~

作者(Author): 张丹宁;徐箭;孙元章;廖思阳;柯德平;

Email:

DOI: 10.13335/j.1000-3673.pst.2018.2343

参考文献(References)：

• [1]向萌．大规模风电接入电力系统的备用容量优化决策研究[D]．北京：华北电力大学，2013．
• [2]黄庶，林舜江，刘明波．含风电场和抽水蓄能电站的多目标安全约束动态优化调度[J]．中国电机工程学报，2016,36(1):112-121.Huang Shu,Lin Shunjiang,Liu Mingbo.Multi-objective security constrained dynamic optimal dispatch with wind farms and pumped storage stations[J].Proceedings of the CSEE,2016,36(1):112-121(in Chinese)．
• [3]颜远，林舜江，刘明波．考虑备用动作约束的含风电场电力系统多目标动态优化调度[J]．电网技术，2018,42(2):479-486.Yan Yuan,Lin Shunjiang,Liu Mingbo.Multi-objective optimal dynamic dispatch of power system with wind farms consideringreserve action constraints[J].Power System Technology,2018,42(2):479-486(in Chinese)．
• [4]梁子鹏，陈皓勇，雷佳，等．考虑风电不确定度的风-火-水-气-核-抽水蓄能多源协同旋转备用优化[J]．电网技术，2018,42(7):2111-2119.Liang Zipeng,Chen Haoyong,Lei Jia,et al.A multi-source coordinated spinning reserve model considering wind power uncertainty[J].Power System Technology,2018,42(7):2111-2119(in Chinese)．
• [5]范刘洋，汪可友，吴巍，等．多时间尺度的电力系统鲁棒调度研究[J]．电网技术，2017,41(5):1576-1582.Fan Liuyang,Wang Keyou,Wu Wei,et al.A study of multi-time scale robust schedule and dispatch methodology[J].Power System Technology,2017,41(5):1576-1582(in Chinese)．
• [6]张倩文，王秀丽，杨廷天，等．含风电场电力系统的鲁棒优化调度[J]．电网技术，2017,41(5):1452-1459.Zhang Qianwen,Wang Xiuli,Yang Tingtian,et al.A robust dispatch method for power grid with wind farms[J].Power System Technology,2017,41(5):1452-1459(in Chinese)．
• [7]Jiang H,Xu J,Sun Y Z,et al.Dynamic reserve demand estimation model and cost-effectivity oriented reserve allocation strategy for multi-area system integrated with wind power[J].IET Generation Transmission&Distribution,2018,12(7):1606-1620．
• [8]艾小猛，塔伊尔江·巴合依，杨立滨，等．基于场景集的含风电电力系统旋转备用优化[J]．电网技术，2018,42(3):835-841.Ai Xiaomeng,Tayierjiang B,Yang Libin,et al.Optimizing the spinning reserve in wind power system using scenario method[J].Power System Technology,2018,42(3):835-841(in Chinese)．
• [9]王海冰，戚永志，王承民，等．考虑柔性负荷的两阶段随机优化调度模型[J]．电网技术，2018,42(11):3669-3675.Wang Haibing,Qi Yongzhi,Wang Chengmin,et al.Two-stage stochastic optimal scheduling model considering flexible load[J].Power System Technology,2018,42(11):3669-3675(in Chinese)．
• [10]刘建涛，朱炳铨，马经纬，等．计及可靠性的日前旋转备用容量评估指标[J]．电网技术，2019,43(6):2147-2153.Liu Jiantao,Zhu Bingquan,Ma Jingwei,et al.Study on the evaluation indexes of spinning reserve capacity considering reliability in day-ahead schedule[J].Power System Technology,2019,43(6):2147-2153(in Chinese)．
• [11]王士柏，韩学山，杨明．计及机组备用响应能力的电力系统区间经济调度[J]．中国电机工程学报，2013,33(7):99-108.Wang Shibo,Han Xueshan,Yang Ming.Interval economic dispatch of power system considering unit reserve responsiveness[J].Proceedings of the CSEE,2013,33(7):99-108(in Chinese)．
• [12]Stewart G M,Robertson A,Jonkman J,et al.The creation of a comprehensive metocean data set for offshore wind turbine simulations[J].Wind Energy,2016,19(6):1151-1159．
• [13]Zhang Z S,Sun Y Z,Gao D W,et al.A versatile probability distribution model for wind power forecast errors and its application in economic dispatch[J].IEEE Transactions on Power Systems,2013,28(3):3114-3125．
• [14]马溪原．含风电电力系统的场景分析方法及其在随机优化中的应用[D]．武汉：武汉大学，2014．
• [15]Tuohy A,Meibom P,Denny E,et al.Unit commitment for systems with significant wind penetration[J].IEEE Transactions on Power Systems,2009,24(2):592-601．
• [16]刘天琪．现代电力系统分析理论与方法[M]．北京：中国电力出版社，2016:129-130．
• [17]Gooi H B,Mendes D P,Bell K R W,et al.Optimal scheduling of spinning reserve[J].IEEE Transactions on Power Systems,1999,14(4):1485-1492．
• [18]Jr P G H.Automatic piecewise linearization in ideal plasticity[J].Computer Methods in Applied Mechanics&Engineering,1977,10(3):249-272．
• [19]EirGrid.EirGrid system performance data[Online].Available:http：//www.eirgrid.com/operations/systemperformancedata．
• [20]PJM.PJM data miner 2[Online].Available:http：//dataminer2.pjm.com/feed/hrl_load_metered/definition．
• [21]Bruninx K,Bergh K V D,Delarue E,et al.Optimization and allocation of spinning reserves in a low-carbon framework[J].IEEETransactions on Power Systems,2015,31(2):872-882．
• [22]Wang C,Lu Z,Qiao Y.A consideration of the wind power benefits in day-ahead scheduling of wind-coal intensive power systems[J].IEEE Transactions on Power Systems,2013,28(1):236-245．
• [23]Starke M R,Kirby B J,Kueck J D,et al.Providing reliability services through demand response:a prelimnary evaluation of the demand response capabilities of alcoa inc[R].Office of Scientific&Technical Information Technical Reports,2009．
• [24]Meterd Load Dara,PJM,Qiao Y.Http：//www.pjm.com/markets-andoperations/ops-analysis/historical-load-data．
• [25]Wang J,Botterud A,Bessa R,et al.Wind power forecasting uncertainty and unit commitment[J].Applied Energy,2011,88(11):4014-4023．
• [26]Padhy N P.Unit commitment-a bibliographical survey[J].IEEETransactions on Power Systems,2004,19(2):1196-1205.