基于相依关系的新能源功率预测场景生成及调度应用
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摘要
新能源日前功率预测对指导电网计划编制具有重要意义,但目前预测水平制约了预测结果的充分应用,为此文中提出新能源功率预测的场景生成方法和预测结果纳入调度计划编制的思路。首先,通过对比分析新能源发电功率和预测功率的边缘分布,建立了揭示二者相依结构的Copula模型,并提出了基于相依关系的多预测场景建模方法。随后,通过分析预测偏差对供电平衡的影响,利用多场景下不同时段预测偏差的规律,提出了将预测可信度纳入省级电网调度计划编制的方法。相关成果已经在国家电网公司西北电力调控分中心得到实际应用,在新能源纳入备用的基础上,采取优化常规电源运行方式、合理组织交易互济等措施,2017年增发新能源电量为4.7 TW·h,降低了3%的受阻率,为新能源纳入电网调度计划编制提供了依据。
The day-ahead forecasting of renewable energy is significant for guiding preparation of power grid planning,but the current prediction accuracy restricts the full application of prediction results.The idea of scenario generation method for renewable energy prediction and prediction consequence which is added into dispatch plan is proposed.Firstly,by comparing and analyzing marginal distribution of generated power and predictive power for renewable energy,a Copula model is established to reveal the dependence relationship between two distributions. Meanwhile,the multi-prediction scenario simulation method based on the dependence relationship is presented.Secondly,the method which integrates the reliability of prediction into provincial power grid dispatch plan is put forward by analyzing the impact of prediction deviation on power supply balance and the law of prediction deviations in multiple scenarios.The relevant results have been applied in the northwest power control sub-center of State Grid Corporation of China.On the basis of the reserve for renewable energy,the measurements which utilizes optimization of operation for conventional power resources,organizes transaction of power market are taken.In 2017,the renewable energy generating capacity is increased by 4.7 GW·h and the blocking rate is reduced by3%,which provides a potent support of incorporating renewable energy into the power grid dispatching plan.
The day-ahead forecasting of renewable energy is significant for guiding preparation of power grid planning,but the current prediction accuracy restricts the full application of prediction results.The idea of scenario generation method for renewable energy prediction and prediction consequence which is added into dispatch plan is proposed.Firstly,by comparing and analyzing marginal distribution of generated power and predictive power for renewable energy,a Copula model is established to reveal the dependence relationship between two distributions. Meanwhile,the multi-prediction scenario simulation method based on the dependence relationship is presented.Secondly,the method which integrates the reliability of prediction into provincial power grid dispatch plan is put forward by analyzing the impact of prediction deviation on power supply balance and the law of prediction deviations in multiple scenarios.The relevant results have been applied in the northwest power control sub-center of State Grid Corporation of China.On the basis of the reserve for renewable energy,the measurements which utilizes optimization of operation for conventional power resources,organizes transaction of power market are taken.In 2017,the renewable energy generating capacity is increased by 4.7 GW·h and the blocking rate is reduced by3%,which provides a potent support of incorporating renewable energy into the power grid dispatching plan.
引文
[1]舒印彪,张智刚,郭剑波,等.新能源消纳关键因素分析及解决措施研究型[J].中国电机工程学报,2017,37(1):1-8.SHU Yinbiao,ZHANG Zhigang,GUO Jianbo,et al.Study on key factors and solution of renewable energy accommodation[J].Proceedings of the CSEE,2017,37(1):1-8.
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[9]王守相,陈海文,李小平,等.风电和光伏随机场景生成的条件变分自动编码器方法[J].电网技术,2018,42(6):191-200.WANG Shouxiang,CHEN Haiwen,LI Xiaoping,et al.Conditional variational automatic encoder method for stochastic scenario generation of wind power and photovoltaic system[J].Power System Technology,2018,42(6):191-200.
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[11]丁明,解蛟龙,刘新宇,等.面向风电接纳能力评价的风资源/负荷典型场景集生成方法与应用[J].中国电机工程学报,2016,36(15):4064-4071.DING Ming,XIE Jiaolong,LIU Xinyu,et al.The generation method and application of wind resources/load typical scenario set for evaluation of wind power grid integration[J].Proceedings of the CSEE,2016,36(15):4064-4071.
[12]徐箭,洪敏,孙元章,等.基于经验Copula函数的多风电场出力动态场景生成方法及其在机组组合中的应用[J].电力自动化设备,2017,37(8):81-89.XU Jian,HONG Min,SUN Yuanzhang,et al.Dynamic scenario generation based on empirical Copula function for outputs of multiple wind farms and its application in unit commitment[J].Electric Power Automation Equipment,2017,37(8):81-89.
[13]贾文昭,康重庆,李丹,等.基于日前风功率预测的风电消纳能力评估方法[J].电网技术,2012,36(8):69-75.JIA Wenzhao,KANG Chongqing,LI Dan,et al.Evaluation on capability of wind power accommodation based on its dayahead forecasting[J].Power System Technology,2012,36(8):69-75.
[14]朱丹丹,刘文颖,蔡万通,等.风电消纳目标下基于电量与功率滚动优化的荷源控制方法[J].电力系统自动化,2018,42(5):80-85.DOI:10.7500/AEPS20170309012.ZHU Dandan,LIU Wenying,CAI Wantong,et al.Loadsource coordinated dispatch method for promoting wind power accommodation based on rolling optimization of energy and power[J].Automation of Electric Power Systems,2018,42(5):80-85.DOI:10.7500/AEPS20170309012.
[15]舒印彪,薛禹胜,蔡斌,等.关于能源转型分析的评述:(二)不确定性及其应对[J].电力系统自动化.2018,42(10):1-12.DOI:10.7500/AEPS20180417009.SHU Yinbiao,XUE Yusheng,CAI Bin,et al.A review of energy transition analysis:Part two uncertainties and approaches[J].Automation of Electric Power Systems,2018,42(10):1-12.DOI:10.7500/AEPS20180417009.
[16]康重庆,姚良忠.高比例可再生能源电力系统的关键科学问题与理论研究框架[J].电力系统自动化.2017,41(9):2-11.DOI:10.7500/AEPS20170120004.KANG Chongqing,YAO Liangzhong.Key scientific issues and theoretical research framework for power systems with high proportion of renewable energy[J].Automation of Electric Power Systems,2017,41(9):2-11.DOI:10.7500/AEPS20170120004.
[17]国家能源局.风电场理论可发电量与弃风电量评估导则:NB/T31055-2014[S].北京:中国电力出版社,2016.National Energy Administration.Guide on wind farm theoretical energy production and wind energy curtailment evaluation:NB/T 31055-2014[S].Beijing:China Electric Power Press,2016.
[18]丁华杰,宋永华,胡泽春,等.基于风电场功率特性的日前风电预测误差概率分布研究[J].中国电机工程学报,2013,33(34):136-144.DING Huajie,SONG Yonghua,HU Zechun,et al.Probability density function of day-ahead wind power forecast errors based on power curves of wind farms[J].Proceedings of the CSEE,2013,33(34):136-144.
[19]BASIT A,HANSEN A D,SORENSEN P E,et al.Real-time impact of power balancing on power system operation with large scale integration of wind power[J].Journal of Modern Power Systems and Clean Energy,2017,5(2):202-210.
[20]盛骤,谢式千,潘承毅.概率论与数理统计[M].北京:高等教育出版社,2001.SHENG Zhou,XIE Shiqian,PAN Chengyi.Probability and statistics[M].Beijing:High Education Press,2001.
[21]张玥,王秀丽,曾平良,等.基于Copula理论考虑风电相关性的源网协调规划[J].电力系统自动化,2017,41(9):80-85.DOI:10.7500/AEPS20160717006.ZHANG Yue,WANG Xiuli,ZENG Pingliang,et al.Copula theory based generation and transmission co-planning considering wind power correlation[J].Automation of Electric Power Systems,2017,41(9):80-85.DOI:10.7500/AEPS20160717006.
[22]兰飞,农植贵,黎静华.风电功率序列的时空相关性研究[J].电力系统及其自动化学报,2016,28(1):24-31.LAN Fei,NONG Zhigui,LI Jinghua.Research on spatial and temporal correlation of wind power sequence[J].Proceedings of the CSU-EPSA,2016,28(1):24-31.
[23]张宁,康重庆.风电出力分析中的相依概率性序列运算[J].清华大学学报,2012,52(5):704-709.ZHANG Ning,KANG Chongqing.Dependent probabilistic sequence operations for wind power output analysis[J].Journal of Tsinghua University Science and Technology,2012,52(5):704-709.
[24]蔡菲,严正,赵静波,等.基于Copula理论的风电场间风速及输出功率相依结构建模[J].电力系统自动化,2013,37(17):9-16.CAI Fei,YAN Zheng,ZHAO Jingbo,et al.Dependence structure models for wind speed and wind power among different wind farms based on Copula theory[J].Automation of Electric Power Systems,2013,37(17):9-16.
[25]韦艳华,张世英.Copula理论及其在金融分析上的应用[M].北京:清华大学出版社,2008.WEI Yanhua,ZHANG Shiying.Copula theory and its application in financial analysis[M].Beijing:Tsinghua University Press,2008.
[26]袁晓建,吕书龙.基于抽样数据与核估计的随机数生成法[J].福建工程学院学报,2014,12(6):595-598.YUAN Xiaojian,LShulong.Random number generation methods based on data sampling and kernel estimation[J].Journal of Fujian University of Technology,2014,12(6):595-598.
[27]国家质量监督检验检疫总局,国家标准化管理委员会.电网运行准则:GB/T 31464-2015[S].北京:中国标准出版社,2015.State Administration for Market Regulation,Standardization Administration.The grid operation code:GB/T 31464-2015[S].Beijing:Standards Press of China,2015.
[28]DEMPSTER H.Risk management:value at risk and beyond[M].Cambridge:Cambridge University Press,2002.
[2]NIESLSEN T S,MADSEN H.WPPT-a tool for wind power prediction[C]//EWEA Special Topic Conference,September25-27,2000,Kassel,Germany.
[3]BAILEY B,BROWER M C,ZACK J.Short-term wind forecasting[C]//European Wind Energy Conference,March 1-5,1999,Nice,France.
[4]薛禹胜,郁琛,赵俊华,等.关于短期及超短期风电功率预测的评述[J].电力系统自动化,2015,39(6):141-151.XUE Yusheng,YU Chen,ZHAO Junhua,et al.A review on short-term and ultra-short-term wind power prediction[J].Automation of Electric Power Systems,2015,39(6):141-151.
[5]吴问足,乔颖,鲁宗相,等.风电功率概率预测方法及展望[J].电力系统自动化,2017,41(18):167-175.DOI:10.7500/AEPS20160914002.WU Wenzu,QIAO Ying,LU Zongxiang,et al.Methods and prospects for probabilistic forecasting of wind power[J].Automation of Electric Power Systems,2017,41(18):167-175.DOI:10.7500/AEPS20160914002.
[6]杨茂,杜刚.基于t location-scale分布的风电功率概率预测研究[J].中国电力,2017,50(1):140-145.YANG Mao,DU Gang.Wind power probability prediction based on t location-scale distribution[J].Electric Power,2017,50(1):140-145.
[7]甘迪,柯德平,孙元章,等.考虑爬坡特性的短期风电功率概率预测[J].电力自动化设备,2016,36(4):145-150.GAN Di,KE Deping,SUN Yuanzhang,et al.Short-term probabilistic wind power forecast considering ramp characteristics[J].Electric Power Automation Equipment,2016,36(4):145-150.
[8]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 method of wind power time series based on fluctuation characteristics[J].Power System Technology,2015,39(1):208-214.
[9]王守相,陈海文,李小平,等.风电和光伏随机场景生成的条件变分自动编码器方法[J].电网技术,2018,42(6):191-200.WANG Shouxiang,CHEN Haiwen,LI Xiaoping,et al.Conditional variational automatic encoder method for stochastic scenario generation of wind power and photovoltaic system[J].Power System Technology,2018,42(6):191-200.
[10]王群,董文略,杨莉.基于Wasserstein距离和改进K-medoids聚类的风电/光伏经典场景集生成算法[J].中国电机工程学报,2015,35(11):2654-2661.WANG Qun,DONG Wenlue,YANG Li.A wind power/photovoltaic typical scenario set generation algorithm based on Wasserstein distance metric and revised K-medoids cluster[J].Proceedings of the CSEE,2015,35(11):2654-2661.
[11]丁明,解蛟龙,刘新宇,等.面向风电接纳能力评价的风资源/负荷典型场景集生成方法与应用[J].中国电机工程学报,2016,36(15):4064-4071.DING Ming,XIE Jiaolong,LIU Xinyu,et al.The generation method and application of wind resources/load typical scenario set for evaluation of wind power grid integration[J].Proceedings of the CSEE,2016,36(15):4064-4071.
[12]徐箭,洪敏,孙元章,等.基于经验Copula函数的多风电场出力动态场景生成方法及其在机组组合中的应用[J].电力自动化设备,2017,37(8):81-89.XU Jian,HONG Min,SUN Yuanzhang,et al.Dynamic scenario generation based on empirical Copula function for outputs of multiple wind farms and its application in unit commitment[J].Electric Power Automation Equipment,2017,37(8):81-89.
[13]贾文昭,康重庆,李丹,等.基于日前风功率预测的风电消纳能力评估方法[J].电网技术,2012,36(8):69-75.JIA Wenzhao,KANG Chongqing,LI Dan,et al.Evaluation on capability of wind power accommodation based on its dayahead forecasting[J].Power System Technology,2012,36(8):69-75.
[14]朱丹丹,刘文颖,蔡万通,等.风电消纳目标下基于电量与功率滚动优化的荷源控制方法[J].电力系统自动化,2018,42(5):80-85.DOI:10.7500/AEPS20170309012.ZHU Dandan,LIU Wenying,CAI Wantong,et al.Loadsource coordinated dispatch method for promoting wind power accommodation based on rolling optimization of energy and power[J].Automation of Electric Power Systems,2018,42(5):80-85.DOI:10.7500/AEPS20170309012.
[15]舒印彪,薛禹胜,蔡斌,等.关于能源转型分析的评述:(二)不确定性及其应对[J].电力系统自动化.2018,42(10):1-12.DOI:10.7500/AEPS20180417009.SHU Yinbiao,XUE Yusheng,CAI Bin,et al.A review of energy transition analysis:Part two uncertainties and approaches[J].Automation of Electric Power Systems,2018,42(10):1-12.DOI:10.7500/AEPS20180417009.
[16]康重庆,姚良忠.高比例可再生能源电力系统的关键科学问题与理论研究框架[J].电力系统自动化.2017,41(9):2-11.DOI:10.7500/AEPS20170120004.KANG Chongqing,YAO Liangzhong.Key scientific issues and theoretical research framework for power systems with high proportion of renewable energy[J].Automation of Electric Power Systems,2017,41(9):2-11.DOI:10.7500/AEPS20170120004.
[17]国家能源局.风电场理论可发电量与弃风电量评估导则:NB/T31055-2014[S].北京:中国电力出版社,2016.National Energy Administration.Guide on wind farm theoretical energy production and wind energy curtailment evaluation:NB/T 31055-2014[S].Beijing:China Electric Power Press,2016.
[18]丁华杰,宋永华,胡泽春,等.基于风电场功率特性的日前风电预测误差概率分布研究[J].中国电机工程学报,2013,33(34):136-144.DING Huajie,SONG Yonghua,HU Zechun,et al.Probability density function of day-ahead wind power forecast errors based on power curves of wind farms[J].Proceedings of the CSEE,2013,33(34):136-144.
[19]BASIT A,HANSEN A D,SORENSEN P E,et al.Real-time impact of power balancing on power system operation with large scale integration of wind power[J].Journal of Modern Power Systems and Clean Energy,2017,5(2):202-210.
[20]盛骤,谢式千,潘承毅.概率论与数理统计[M].北京:高等教育出版社,2001.SHENG Zhou,XIE Shiqian,PAN Chengyi.Probability and statistics[M].Beijing:High Education Press,2001.
[21]张玥,王秀丽,曾平良,等.基于Copula理论考虑风电相关性的源网协调规划[J].电力系统自动化,2017,41(9):80-85.DOI:10.7500/AEPS20160717006.ZHANG Yue,WANG Xiuli,ZENG Pingliang,et al.Copula theory based generation and transmission co-planning considering wind power correlation[J].Automation of Electric Power Systems,2017,41(9):80-85.DOI:10.7500/AEPS20160717006.
[22]兰飞,农植贵,黎静华.风电功率序列的时空相关性研究[J].电力系统及其自动化学报,2016,28(1):24-31.LAN Fei,NONG Zhigui,LI Jinghua.Research on spatial and temporal correlation of wind power sequence[J].Proceedings of the CSU-EPSA,2016,28(1):24-31.
[23]张宁,康重庆.风电出力分析中的相依概率性序列运算[J].清华大学学报,2012,52(5):704-709.ZHANG Ning,KANG Chongqing.Dependent probabilistic sequence operations for wind power output analysis[J].Journal of Tsinghua University Science and Technology,2012,52(5):704-709.
[24]蔡菲,严正,赵静波,等.基于Copula理论的风电场间风速及输出功率相依结构建模[J].电力系统自动化,2013,37(17):9-16.CAI Fei,YAN Zheng,ZHAO Jingbo,et al.Dependence structure models for wind speed and wind power among different wind farms based on Copula theory[J].Automation of Electric Power Systems,2013,37(17):9-16.
[25]韦艳华,张世英.Copula理论及其在金融分析上的应用[M].北京:清华大学出版社,2008.WEI Yanhua,ZHANG Shiying.Copula theory and its application in financial analysis[M].Beijing:Tsinghua University Press,2008.
[26]袁晓建,吕书龙.基于抽样数据与核估计的随机数生成法[J].福建工程学院学报,2014,12(6):595-598.YUAN Xiaojian,LShulong.Random number generation methods based on data sampling and kernel estimation[J].Journal of Fujian University of Technology,2014,12(6):595-598.
[27]国家质量监督检验检疫总局,国家标准化管理委员会.电网运行准则:GB/T 31464-2015[S].北京:中国标准出版社,2015.State Administration for Market Regulation,Standardization Administration.The grid operation code:GB/T 31464-2015[S].Beijing:Standards Press of China,2015.
[28]DEMPSTER H.Risk management:value at risk and beyond[M].Cambridge:Cambridge University Press,2002.