基于风-浪和灰色模型的波浪能发电系统输出功率短期预测
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摘要
波浪能具有随机波动性,会对波浪能发电并网以及电力系统的安全稳定产生重要影响,准确预测波浪能可为电力调度控制带来极大便利。提出基于风-浪和灰色模型的波浪能发电系统功率预测方法,在波功率历史数据不足或缺省的情况下,能够依据风浪相关性及风速历史数据有效预测波浪功率。首先分析了风与波浪的相关性和时延特性,建立风-浪经验模型对波高进行短期预测,并利用灰色GM(1,1)模型对波浪短期预测结果进行残差修正。在此基础上,基于直驱式波浪能发电系统分析并建立了波高-功率转换模型。通过实例分析对波浪能发电功率的预测结果进行了验证。
Wave is fluctuant,and its volatility and uncertainty will have impacts on the grid-connection of wave energy generation system and the reliable and safe operation of power system. The accurate output power prediction of wave energy generation system can bring great convenience to the control and dispatching of power system. A prediction method based on the wind-wave and grey model is proposed. When the historical data of wave power is insufficient or default,it can effectively predict the output power of wave energy generation system according to the windwave correlation and historical data of wind speed. The wind-wave correlation and the time-delay characteristic are analyzed,and the wind-wave empirical model is established to predict the short-term wave height,with further residual correction using grey GM( 1,1) model. Based on the direct-drive wave energy generation system,the transformation model between wave height and wave power is built. Using the measured data of wind and wave,the output power of wave energy generation system is predicted,and the proposed models are validated.
Wave is fluctuant,and its volatility and uncertainty will have impacts on the grid-connection of wave energy generation system and the reliable and safe operation of power system. The accurate output power prediction of wave energy generation system can bring great convenience to the control and dispatching of power system. A prediction method based on the wind-wave and grey model is proposed. When the historical data of wave power is insufficient or default,it can effectively predict the output power of wave energy generation system according to the windwave correlation and historical data of wind speed. The wind-wave correlation and the time-delay characteristic are analyzed,and the wind-wave empirical model is established to predict the short-term wave height,with further residual correction using grey GM( 1,1) model. Based on the direct-drive wave energy generation system,the transformation model between wave height and wave power is built. Using the measured data of wind and wave,the output power of wave energy generation system is predicted,and the proposed models are validated.
引文
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[15]秦川,管维亚,鞠平,等.并网AWS波浪发电场等效建模[J].电力自动化设备,2015,35(11):25-31.QIN Chuan,GUAN Weiya,JU Ping,et al.Equivalent modeling of AWS-based wave farm[J].Electric Power Automation Equipment,2015,35(11):25-31.
[16]POLINDER H,DAMEN M E C,GARDNER F.Linear PM Generator system for wave energy conversion in the AWS[J].IEEE Transactions on Energy Conversion,2000,19(3):583-589.
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[18]尤再进,尹宝树,石洪源.应用“跨零-能量”法估算海洋波浪再生能资源[J].海洋与湖沼,2017,48(5):926-931.YOU Zaijin,YIN Baoshu,SHI Hongyuan.New wave analysis method“Zero Crossing-Energy Balance”for estimation of renewable ocean wave energy[J].Oceanologia Et Limnologia Sinica,2017,48(5):926-931.
[2]张洪生,辜俊波,王海龙,等.利用WAVEWATCH和SWAN嵌套计算珠江口附近海域的风浪场[J].热带海洋学报,2013,32(1):8-17.ZHANG Hongsheng,GU Junbo,WANG Hailong,et al.Simulating wind wave field near the Pearl River Estuary with SWAN nested in WAVEWATCH[J].Journal of Tropical Oceanography,2013,32(1):8-17.
[3]霍政界,吴峰,陶爱峰,等.直驱式波浪发电系统输出功率的短期预测[J].电力系统自动化,2014,38(21):13-18.HUO Zhengjie,WU Feng,TAO Aifeng,et al.Short-term prediction on output power of direct-drive wave power generation system[J].Automation of Electric Power Systems,2014,38(21):13-18.
[4]SCHOEN M P,HALS J,MOAN T.Wave prediction and robust control of heaving wave energy devices for irregular waves[J].IEEE Transactions on Energy Conversion,2011,26(2):627-638.
[5]CUADRA L,SALCEDO-SANZ S,NIETO-BORGE J C,et al.Computational intelligence in wave energy:comprehensive review and case study[J].Renewable&Sustainable Energy Reviews,2016,58:1223-1246.
[6]CORNEGO-BUENO L,NIETO-BORGE J C,GARCIA-DIAZ P,et al.Significant wave height and energy flux prediction for marine energy applications:a grouping genetic algorithm-extreme learning machine approach[J].Renewable Energy,2016,97:380-389.
[7]ZGER M.Prediction of ocean wave energy from meteorological variables by fuzzy logic modeling[J].Expert Systems with Applications,2011,38(5):6269-6274.
[8]TRUONG D Q,AHN K K.Wave prediction based on a modified grey model MGM(1,1)for real-time control of wave energy converters in irregular waves[J].Renewable Energy,2012,43(6):242-255.
[9]黄元生,方伟.基于灰色傅里叶变换残差修正的电力负荷预测模型[J].电力自动化设备,2013,33(9):105-107,112.HUANG Yuansheng,FANG Wei.Power load forecasting model with residual error correction based on gray Fourier transform[J].Electric Power Automation Equipment,2013,33(9):105-107,112.
[10]郭佳.并网型光伏电站发电功率与其主气象影响因子相关性分析[D].保定:华北电力大学,2013.GUO Jia.Correlation analysis between generation power and main meteorological factors of grid-connected PV power system[D].Baoding:North China Electric Power University,2013.
[11]李伦,吴雄斌,徐兴安,等.高频地波雷达风速反演经验模型[J].武汉大学学报(信息科学版),2012,37(9):1096-1099.LI Lun,WU Xiongbin,XU Xingan,et al.An empirical model for wind speed inversion by HFSWR[J].Geomatics and Information Science of Wuhan University,2012,37(9):1096-1099.
[12]王子赟,纪志成.基于灰色辨识模型的风电功率短期预测[J].电力系统保护与控制,2013,41(12):79-85.WANG Ziyun,JI Zhicheng.Grey-identification model based wind power generation short-term prediction[J].Power System Protection and Control,2013,41(12):79-85.
[13]黄宣睿,孙凯,肖曦.基于平均功率估算的直驱海浪发电最大功率点跟踪控制方法[J].电力系统自动化,2016,40(14):51-57.HUANG Xuanrui,SUN Kai,XIAO Xi.Maximum power pointtracking control method for direct-drive wave energy generation based on average power estimation[J].Automation of Electric Power Systems,2016,40(14):51-57.
[14]杨斌,冯卫兵,虞丹君.江苏辐射沙洲北部海域风浪关系分析[J].水道港口,2014,35(6):578-581.YANG Bin,FENG Weibing,YU Danjun.Analysis on wind-wave relationship on north coastal waters of Jiangsu radial sand ridges[J].Journal of Waterway and Harbor,2014,35(6):578-581.
[15]秦川,管维亚,鞠平,等.并网AWS波浪发电场等效建模[J].电力自动化设备,2015,35(11):25-31.QIN Chuan,GUAN Weiya,JU Ping,et al.Equivalent modeling of AWS-based wave farm[J].Electric Power Automation Equipment,2015,35(11):25-31.
[16]POLINDER H,DAMEN M E C,GARDNER F.Linear PM Generator system for wave energy conversion in the AWS[J].IEEE Transactions on Energy Conversion,2000,19(3):583-589.
[17]PRADO M G D S,GARDNER F,DAMEN M,et al.Modeling and test results of the Archimedes wave swing[J].Proceedings of the Institution of Mechanical Engineers.Part A.Journal of Power&Energy,2006,220(8):855-868.
[18]尤再进,尹宝树,石洪源.应用“跨零-能量”法估算海洋波浪再生能资源[J].海洋与湖沼,2017,48(5):926-931.YOU Zaijin,YIN Baoshu,SHI Hongyuan.New wave analysis method“Zero Crossing-Energy Balance”for estimation of renewable ocean wave energy[J].Oceanologia Et Limnologia Sinica,2017,48(5):926-931.