基于超短期风电预测和混合储能的风电爬坡优化控制Optimal Control of Wind Ramp Based on Very Short-Term Wind Forecast and Hybrid ESS
何川;刘天琪;胡晓通;李茜;李兴源;
摘要(Abstract):
风电爬坡对电力系统运行的经济性和可靠性有较大的影响,也是对电网造成冲击的重要因素之一,如何减小风电爬坡时的功率波动对电网的冲击成为国内外研究热点。为风电场配备储能系统能够有效抑制风电爬坡时的功率波动。为此,提出一种基于风电功率超短期预测和混合储能系统实现平抑功率在电池和超级电容器之间有效分配方法。首先通过奇异值分解理论风电爬坡事件,提出混合储能系统的动态最佳荷电状态,以使储能设备更好地平抑下一时段风电功率波动。考虑未来风电功率及其预测误差,根据超前充放电控制策略对储能设备当前充放电进行修正,并给出了提前充放电修正公式。仿真结果表明,该方法及其控制策略能有效抑制风电爬坡的功率波动,从而减小风电爬坡事件对电网的冲击,并且能够充分提高混合储能设备的利用效率。
关键词(KeyWords): 风电爬坡事件;功率波动;超短期预测;混合储能系统;荷电状态;超前控制策略
基金项目(Foundation): 四川省科技支撑计划项目(2016GZ0143)~~
作者(Author): 何川;刘天琪;胡晓通;李茜;李兴源;
Email:
DOI: 10.13335/j.1000-3673.pst.2016.1541
参考文献(References):
- [1]张丽英,叶廷路,辛耀中,等.大规模风电接入电网的相关问题及措施[J].中国电机工程学报,2010,30(25):1-9.Zhang Liying,Ye Tinglu,Xin Yaozhong,et al.Problems and measures of power grid accommodating large scale wind power[J].Proceedings of the CSEE,2010,30(25):1-9(in Chinese).
- [2]李蓓,郭剑波.平抑风电功率的电池储能系统控制策略[J].电网技术,2012,36(8):38-43.Li Bei,Guo Jianbo.A control strategy for battery energy storage system to level wind power output[J].Power System Technology,2012,36(8):38-43(in Chinese).
- [3]王铮,王伟胜,刘纯,等.基于风过程方法的风电功率预测结果不确定性估计[J].电网技术,2013,37(1):242-247.Wang Zheng,Wang Weisheng,Liu Chun,et al.Uncertainty estimation of wind power prediction result based on wind process method[J].Power System Technology,2013,37(1):242-247(in Chinese).
- [4]丁明,林根德,陈自年,等.一种适用于混合储能系统的控制策略[J].中国电机工程学报,2012,32(7):1-6.Ding Ming,Lin Gende,Chen Zinian,et al.A control strategy for hybrid energy storage systems[J].Proceedings of the CSEE,2012,32(7):1-6(in Chinese).
- [5]孙承晨,袁越,San Shing Choi,等.基于经验模态分解和神经网络的微网混合储能容量优化配置[J].电力系统自动化,2015,39(8):19-26.Sun Chengchen,Yuan Yue,San Shing Choi.Capacity optimization of hybrid energy storage systems in microgrid using empirical mode decomposition and neural network[J].Automation of Electric Power Systems,2015,39(8):19-26(in Chinese).
- [6]吕超贤,李欣然,户龙辉,等.基于小波分频与双层模糊控制的多类型储能系统平滑策略[J].电力系统自动化,2015,39(2):21-29.LüChaoxian,Li Xinran,Hu Longhui,et al.A smoothing strategy for hybrid energy storage system based on wavelet frequency allocation and two-level fuzzy control[J].Automation of Electric Power Systems,2015,39(2):21-29(in Chinese).
- [7]韩晓娟,陈跃燕,张浩,等.基于小波包分解的混合储能技术在平抑风电场功率波动中的应用[J].中国电机工程学报,2013,33(19):8-13.Han Xiaojuan,Chen Yueyan,Zhang Hao,et al.Application of hybrid energy storage technology based on wavelet packet decomposition in smoothing the fluctuations of wind power[J].Proceedings of the CSEE,2013,33(19):8-13(in Chinese).
- [8]娄素华,吴耀武,崔艳昭,等.电池储能平抑短期风电功率波动运行策略[J].电力系统自动化,2014,38(2):17-22.Lou Suhua,Wu Yaowu,Cui Yanzhao,et al.Operation strategy of battery energy storage system for smoothing short-term wind power fluctuation[J].Automation of Electric Power Systems,2014,38(2):17-22(in Chinese).
- [9]柴炜,曹云峰,李征,等.基于状态量预测的风储联合并网储能优化控制方法[J].电力系统自动化,2015,39(2):13-20.Chai Wei,Cao Yunfeng,Li Zheng,et al.An optimal energy storage control scheme for wind power and energy storage system based on state forecast[J].Automation of Electric Power Systems,2015,39(2):13-20(in Chinese).
- [10]闫鹤鸣,李相俊,麻秀范,等.基于超短期风电预测功率的储能系统跟踪风电计划出力控制方法[J].电网技术,2015:39(2):432-439.Yan Heming,Li Xiangjun,Ma Xiufan,et al.Wind power output schedule tracking control method of energy storage system based on ultra-short term wind power prediction[J].Power System Technology,2015:39(2):432-439(in Chinese).
- [11]戚永志,刘玉田.风电高风险爬坡有限度控制[J].中国电机工程学报,2013,33(13):69-75.Qi Yongzhi,Liu Yutian.Finite control of high risk wind power ramping[J].Proceedings of the CSEE,2013,33(13):69-75(in Chinese).
- [12]Francis N.Predicting sudden changes in wind power generation[J].North American Wind Power,2008,5(9):58-60.
- [13]欧阳庭辉,查晓明,秦亮,等.风电功率爬坡事件预测时间窗选取建模[J].中国电机工程学报,2015,35(13):3204-3210.Ouyang Tinghui,Zha Xiaoming,Qin Liang,et al.Modeling on selection of the time window for ramp events prediction[J].Proceedings of the CSEE,2015,35(13):3204-3210(in Chinese).
- [14]戚永志,刘玉田.基于竞争博弈的风电爬坡协同控制策略[J].中国电机工程学报,2014,34(24):4341-4349.Qi Yongzhi,Liu Yutian.Ramping coordination control of wind generation based on competitive game theory[J].Proceedings of the CSEE,2014,34(24):4341-4349(in Chinese).
- [15]王颖,张凯锋,付嘉渝,等.抑制风电爬坡率的风储联合优化控制方法[J].电力系统自动化,2013,37(13):17-23.Wang Ying,Zhang Kaifeng,Fu Jiayu,et al.Optimization control method of wind/storage system for suppressing wind power ramp rate[J].Automation of Electric Power Systems,2013,37(13):17-23(in Chinese).
- [16]Lee D,Kim J,Baldick R.Stochastic optimal control of the storage system to limit ramp rates of wind power output[J].IEEE Transactions on Smart Grid,2013,4(4):2256-2265.
- [17]赵学智,叶邦彦.SVD和小波变换的信号处理效果相似性及其机理分析[J].电子学报,2008,36(8):1582-1589.Zhao Xuezhi,Ye Bangyan.The similarity of signal processing effect between SVD and wavelet transform and its mechanism analysis[J].Acta Electronica Sinica,2008,36(8):1582-1589(in Chinese).
- [18]裴益轩,郭民.滑动平均法的基本原理及应用[J].火炮发射与控制学报,2001(1):21-23.Pei Yixuan,Guo Min.The Fundamental principle and application of sliding average method[J].Gun Launch&Control Journal,2001(1):21-23(in Chinese).
- [19]张文亮,丘明,来小康.储能技术在电力系统中的应用[J].电网技术,2008,32(7):1-9.Zhang Wenliang,Qiu Ming,Lai Xiaokang.Application of energy storage technologies in power grids[J].Power System Technology,2008,32(7):1-9(in Chinese).
- [20]Kamath C.Understanding wind ramp events through analysis of historical data[C]//Transmission and Distribution Conference and Exposition.New Orleans,LA,USA:IEEE,2010:1-6.
- [21]Ferreira C,Gama J,Matias L,et al.A survey on wind power ramp forecasting[R].Argonne,IL USA:Argonne National Laboratory(ANL),2011.
- [22]IEM:AWOS one minute data download[EB/OL].Ames,IA,USA:Iowa State University of Science and Technology.2001[2015-04-30].https://mesonet.agron.iastate.edu/request/awos/1min.php.
- [23]王境彪,晁勤,王一波,等.基于主次双尺度交集切割效应的混合储能平抑风功率波动控制[J].电网技术,2015,39(12):3370-3377.Wang Jingbiao,Chao Qin,Wang Yibo,et al.A control of hybrid energy storage system for suppressing fluctuation of wind power based on primary-secondary scale intersection cutting effect[J].Power System Technology,2015,39(12):3370-3377(in Chinese).
- [24]刘辉,田红旗,李燕飞.基于小波分析法与滚动式时间序列法的风电场风速短期预测优化算法[J].中南大学学报(自然科学版),2010,41(1):370-375.Liu Hui,Tian Hongqi,Li Yanfei.Short-term forecasting optimization algorithm for wind speed from wind farms based on wavelet analysis method and rolling time series method[J].Journal of Central South University(Science and Technology),2010,41(1):370-375(in Chinese).