基于NARX模型的光伏并网逆变器非线性模型辨识方法
A Nonlinear Model Identification Method of Photovoltaic Grid-Connected Inverters Based on the NARX Model

作者: 郑 伟 :广东电网有限责任公司湛江供电局,广东 湛江;

关键词: 光伏逆变器系统辨识NARX黑箱Photovoltaic Inverter System Identification NARX Black Box

摘要:
论文提出了单相光伏并网逆变器NARX模型的系统辨识方法。针对商用光伏并网逆变器的“黑箱”特征,以及现有的线性化建模方法无法解决逆变器的强非线性问题,将单相光伏并网逆变器视为“黑箱”,无需逆变器内部电路、功率开关器件等拓扑结构和参数及其控制系统的类型和逻辑关系,仅仅利用逆变器输入–输出两侧的外部测量数据,基于NARX模型非线性系统辨识技术,可建立较为准确的数学模型,实现对商用光伏并网逆变器准确描述其动态特性的可能。辨识所得单相光伏并网逆变器NARX模型结构简单,运算量小,在模型的复杂性和模型的精确性方面取了很好的平衡,适用于电力系统对并网光伏发电系统的调度、联合运行与协调控制、随机模拟等需要快速建模与简单模型结构的研究领域。

Abstract: The system identification method of single-phase photovoltaic grid-connected inverter NARX model was proposed. For the black box feature of commercial photovoltaic grid-tied inverters, as well as the strongly nonlinear problem of the inverter which cannot be solved by existing linear modeling approach, in this method, the inverter was considered as a black box, wherein it was not necessary to know the topology and the parameters of the inverter internal circuits and power switching devices, as well as the type and logical relations of the control system. It only used the input-output external measurement data of the inverter, based on the NARX model nonlinear system identification techniques, to create an accurate mathematical model. The model can accurately imitate the behavior of the commercial inverter, and has simple structure and a small amount of computation. It takes a good balance between the complexity of the model and the model accuracy. It is suitable for power system with the grid-connected photovoltaic system scheduling, joint operation and coordinated control, and stochastic simulation research areas, in which the fast modeling and simple model structure are required.

文章引用: 郑 伟 (2015) 基于NARX模型的光伏并网逆变器非线性模型辨识方法。 智能电网, 5, 228-241. doi: 10.12677/SG.2015.55028

参考文献

[1] 刘东冉, 陈树勇, 马敏, 王皓怀, 侯俊贤, 马世英 (2011) 光伏发电系统模型综述. 电网技术, 8, 47-52.

[2] 黄汉奇, 毛承雄, 陆继明, 王丹 (2012) 光伏发电系统的小信号建模与分析述. 中国电机工程学报, 22, 7-14.

[3] 艾欣, 韩晓男, 孙英云 (2013) 大型光伏电站并网特性及其低碳运行与控制技术述. 电网技术, 1, 15-23.

[4] Middlebrook, R.D. and Cuk, S. (1976) A general unified approach to modeling-switching converter power stages. Proceedings of the IEEE Power Electronics Specialists Conference, Cleveland, 8 June 1976, 73-68.

[5] 魏克银, 刘德志, 欧阳斌, 翟小飞, 晏明 (2009) 三相四线制二极管整流桥的动态平均值模型. 电工技术学报, 11, 102-107.

[6] 马西奎, 李明, 戴栋, 张浩, 邹建龙 (2006) 电力电子电路与系统中的复杂行为研究综述. 电工技术学报, 12, 1-11.

[7] Banerjee, S. and Verghese, G.C. (2001) Nonlinear phenomena in power electronics: Attractors, bifurcations, chaos, and nonlinear control. Wiley-IEEE Press, New Jersey.
http://dx.doi.org/10.1109/9780470545393

[8] Tse, C.K. (2004) Complex behavior of switching power converters. CRC Press, Boca Raton.

[9] Tse, C.K. and di Bernardo, M. (2002) Complex behavior in switching power converters. Proceeding of the IEEE, 90, 768-781.
http://dx.doi.org/10.1109/JPROC.2002.1015006

[10] 谢玲玲, 龚仁喜, 李畸勇 (2013) 光伏发电最大功率点跟踪交错并联Boost变换器的动力学特性分析. 中国电机工程学报, 6, 38-45.

[11] Mezghanni, D., Andoulsi, R., Mami, A. and Dauphin-Tanguy, G. (2007) Bond graph modelling of a pho-tovoltaic system feeding an induction motor-pump. Simulation Modelling Practice and Theory, 15, 1224-1238.
http://dx.doi.org/10.1016/j.simpat.2007.08.003

[12] Delgado, M. and Sira-Ramirez, H. (1998) A bond graph ap-proach to the modeling and simulation of switch regulated DC-to-DC power supplies. Simulation Practice and Theory, 6, 631-646.
http://dx.doi.org/10.1016/S0928-4869(98)00011-1

[13] Araújo, R.E., Leite, A.V. and Freitas, D.S. (2002) Model-ling and simulation of power electronic systems using a bond graph formalism. Proceedings of the 10th Mediterranean Conference on Control and Automation (MED 2002), Lisbon, 9-12 July 2002, 1-9.

[14] Smedley, K. and Cuk, S. (1994) Switching flow-graph nonlinear modeling technique. IEEE Transactions on Power Electronics, 9, 405-413.
http://dx.doi.org/10.1109/63.318899

[15] Veerachary, M., Senjyu, T. and Uezato, K. (2003) Signal flow graph modelling of interleaved buck converters. International Journal of Circuit Theory and Applications, 31, 249-264.
http://dx.doi.org/10.1002/cta.230

[16] Castaner, L. and Silvestre, S. (2002) Modelling photovoltaic systems using PSpice. John Wiley & Sons Ltd, Chichester.
http://dx.doi.org/10.1002/0470855541

[17] Biolek, D., Biolkova, V. and Kolka, Z. (2008) Averaged modeling of switched DC-DC converters based on Spice models of semiconductor switches. Proceedings of the 7th WSEAS International Conference on Circuits, Systems, Electronics, Control and Signal Processing (CSECS’08), Puerto de la Cruz, 15-17 December 2008, 162-167.

[18] Onbilgin, G., Ozgonenel, O. and Turkmenoglu, V. (2007) Modeling of power electronics circuits using wavelet theory. Sampling Theory in Signal and Image Processing, 6, 307-322.

[19] 曾正, 赵荣祥, 杨欢 (2012) 含逆变器的微电网动态相量模型. 中国电机工程学报, 10, 65-71.

[20] 张波 (2006) 电力电子学亟待解决的若干基础问题探讨. 电工技术学报, 3, 24-35.

[21] 刘邦银 (2004) 电压源型逆变器的智能控制技术研究. 硕士论文, 华中科技大学, 武汉.

[22] Billings, B.S. and Leontaritis, I.J. (1982) Parameter estimation techniques for nonlinear systems. Proceedings of the 6th IFAC Symposium on Identification and System Parameter Estimation, Washington DC, 7-11 June 1982, 505-510.

[23] Radmaneshfar, E. and Karrari, M. (2007) A new method for structure detection of nonlinear ARX model: ANOVA_BSD. Proceedings of the World Congress on Engineering 2007 (WCE 2007), London, 2-4 July 2007, 407-411.

[24] Beyhan, S. and Alci, M. (2010) Fuzzy functions based ARX model and new fuzzy basis function models for nonlinear system identification. Applied Soft Computing, 10, 439-444.
http://dx.doi.org/10.1016/j.asoc.2009.08.015

[25] Ljung, L. (2002) System identification: Theory for the user. 2nd Edition, Prentice Hall PTR, London.

[26] 郭科, 陈聆, 魏友华 (2007) 最优化方法及其应用. 高等教育出版社, 北京.

[27] 陈艳 (2012) 光伏发电系统中Z源逆变器的控制技术研究. 博士论文, 重庆大学, 重庆.

[28] Ljung, L. (2015) System identification toolbox user’s guide. The MathWorks Inc., Na-tick.

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