基于风电场群汇聚演变趋势的场群持续功率特性预测方法
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摘要
大规模开发、集中外送是我国风电开发的特有模式。由于风力发电具有随机性、波动性及低功率密度等特性,在进行大规模风电联网规划时,易造成输电通道配置过度或不足的问题。持续功率曲线能够有效表征风电场群输出功率的长期波动规律性,准确把握规划目标年风电场集群持续功率特性是科学配置外送输电容量的关键。为此,该文通过深入分析不同规模风电场群功率变化趋势,揭示了风电场群汇聚过程中"装机容量–功率"的关联关系,进而构建风电场群的汇聚演变模型,实现了已知未来风电场群总装机容量的条件下,规划目标年风电场群持续功率特性的准确预测。最后,分别应用东北、西北两大风电基地历史实测数据对预测方法进行校验,结果表明所提方法是易行、有效的。
Large-scale wind power has been developed by constructing wind farm cluster incorporate to grid in China.Generally the power of wind farm cluster has characteristics of intermittency, fluctuation and low power density. Wind power variation should be properly considered in transmission planning for wind farm cluster connect to grid. The main task is to master the characteristics of wind power in the target planning year. This paper reveald the long-term fluctuation regularity of the power of wind farm cluster can be effectively characterized by the wind power duration curve. The cumulative effect, a degressive trend of maximal wind power in per unit with increasing installed capacity of wind farms, was definded. The model of duration curves varing with installed capacity was proposed, to predict durative power characteristics of the target planning year with a given planning wind capacity. Finally, the prediction method was verified by examples of two major wind power clusters in northeast and northwest China. The results show that the proposed method is simple and effective.
Large-scale wind power has been developed by constructing wind farm cluster incorporate to grid in China.Generally the power of wind farm cluster has characteristics of intermittency, fluctuation and low power density. Wind power variation should be properly considered in transmission planning for wind farm cluster connect to grid. The main task is to master the characteristics of wind power in the target planning year. This paper reveald the long-term fluctuation regularity of the power of wind farm cluster can be effectively characterized by the wind power duration curve. The cumulative effect, a degressive trend of maximal wind power in per unit with increasing installed capacity of wind farms, was definded. The model of duration curves varing with installed capacity was proposed, to predict durative power characteristics of the target planning year with a given planning wind capacity. Finally, the prediction method was verified by examples of two major wind power clusters in northeast and northwest China. The results show that the proposed method is simple and effective.
引文
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[2]申颖,赵千川,李明扬.多时空尺度下风电平滑效应的分析[J].电网技术,2015,39(2):400-405.Shen Ying,Zhao Qianchuan,Li Mingyang.Analysis on wind power smoothing effect in multiple temporal and spatial scales[J].Power System Technology,2015,39(2):400-405(in Chinese).
[3]李湃,管晓宏,吴江,等.基于天气分类的风电场群总体出力特性分析[J].电网技术,2015,39(7):1866-1872.Li Pai, Guan Xiaohong, Wu Jiang, et al. Analyzing characteristics of aggregated wind power generation based on weather regime classification[J]. Power System Technology,2015,39(7):1866-1872(in Chinese).
[4] Luo Changling,Bankaarh,Shen Baike,et al.Strategies to smooth wind power fluctuations of wind turbine generator[J].IEEE Trans. on Energy Conversion,2007,22(2):341-349.
[5]张新松,袁越,吴博文,等.电力市场环境下含大规模风电场的输电网规划[J].电力自动化设备,2012,32(4):100-103.Zhang Xinsong,Yuan Yue,Wu Bowen,et al.Expansion planning of transmission network with large wind farm in deregulated electricity market environment[J]. Electric Power Automation Equipment,2012,32(4):100-103(in Chinese).
[6]王茜,张粒子.采用NSGA-Ⅱ混合智能算法的风电场多目标电网规划[J].中国电机工程学报,2011,31(19):17-24.Wang Qian, Zhang Lizi. Multi-objective transmission planning associated with wind farms applying NSGA-II hybrid intelligent algorithm[J].Proceedings of the CSEE,2011,31(19):17-24(in Chinese).
[7]姜惠兰,安星,王亚微,等.基于改进NSGA2算法的考虑风机接入电能质量的多目标电网规划[J].中国电机工程学报,2015,35(21):5405-5411.Jiang Huilan,An Xing,Wang Yawei,et al.Improved NSGA2 algorithm based multi-objective planning of power grid with wind farm considering power quality[J].Proceedings of the CSEE,2015,35(21):5405-5411(in Chinese).
[8] George A O, Pavlos S G. Transmission expansion planning of systems with increasing wind power integration[J]. IEEE Transactions on Power Systems,2013,28(2):1355-1362.
[9] Sturt A,Strbac G.Time series modelling of power output for large-scale wind fleets[J].Wind Energy,2011,14(8):953-966.
[10]黄裕春,杨甲甲,文福拴,等.计及接纳间歇性电源能力的输电系统规划方法[J].电力系统自动化,2013,37(4):28-34.Huang Yuchun, Yang Jiajia, Wen Fushuan, et al.Transmission system planning considering capability of accommodating intermittent generation sources[J].Automation of Electric Power Systems,2013,37(4):28-34(in Chinese).
[11]李驰,刘纯,黄越辉,等.基于波动特性的风电出力时间序列建模方法研究[J].电网技术,2015,39(1):208-214.Li Chi,Liu Chun,Huang Yuehui,et al.Study on the modeling method of wind power time series based on fluctuation characteristics[J].Power System Technology,2015,39(1):208-214(in Chinese).
[12]刘纯,吕振华,黄越辉,等.长时间尺度风电出力时间序列建模新方法研究[J].电力系统保护与控制,2013,41(1):7-13.Liu Chun,LüZhenhua,Huang Yuehui,et al.A new method to simulate wind power time series of large time scale[J].Power System Protection and Control,2013,41(1):7-13(in Chinese).
[13]罗钢,石东源,陈金富,等.风光发电功率时间序列模拟的MCMC方法[J].电网技术,2014,38(2):321-327.Luo Gang,Shi Dongyuan,Chen Jinfu,et al.A Markov chain Monte Carlo method for simulation of wind and solar power time series[J].Power System Technology,2014,38(2):321-327(in Chinese)
[14] Papaefthymiou G, Klockl B. MCMC for wind power simulation[J].IEEE Transaction on Energy Conversion,2007,23(1):234-240.
[15]于鹏,黎静华,文劲宇,等.含风电功率时域特性的风电功率序列建模方法[J].中国电机工程学报,2014,34(22):3715-3723.Yu Peng,Li Jinghua,Wen Jinyu,et al.A wind power time series modeling method based on its time domain characteristics[J]. Proceedings of the CSEE, 2014,34(22):3715-3723(in Chinese).
[16]穆钢,崔杨,严干贵.确定风电场群功率汇聚外送输电容量的静态综合优化方法[J].中国电机工程学报,2011,35(1):15-19.Mu Gang,Cui Yang,Yan Gangui.A static optimization method to determine integrated power transmission capacity of clustering wind farms[J].Proceedings of the CSEE,2011,35(1):15-19(in Chinese).