在弱電網情況下之智慧型控制太陽光發電系統的低電壓穿越控制

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姓名

羅文洲(Wen-Chou Luo) 查詢紙本館藏

畢業系所

電機工程學系

論文名稱

在弱電網情況下之智慧型控制太陽光發電系統的低電壓穿越控制
(LVRT Control of Photovoltaic Power System Using Intelligent Control Under Weak Grid Condition)

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摘要(中)

本論文提出一個用來改善低電壓穿越性能的智慧型控制之雙級太陽光發電系統去處理在弱電網情況下之故障。一般電網的強度與短路比有密切關係，當短路比越低電網的強度越弱。本文太陽光發電系統包含一個交錯式直流至直流轉換器與一個三階層中性點箝位變流器所組成。此外，太陽光發電系統具有智慧型變流器功能，其中太陽光電變流器的輸出實功、虛功是根據電網規範所計算的。為了提高太陽光發電系統的控制性能來處理在弱電網情況下之故障，本文提出了一種線上學習的遞迴式小波模糊類神經網路，用來取代傳統的比例積分控制器用於智慧型變流器的實虛功控制。此外，本文提出的太陽光發電系統的控制器是透過PSIM軟體來模擬。另外，所提出的控制器是使用浮點運算數位訊號處理器的兩個控制平台來實現。從模擬結果與實驗結果可以看出，利用智慧型變流器的智慧型控制，可以實現在弱電網情況下發生故障時實功控制與虛功控制的優良性能。

摘要(英)

An intelligent control method is proposed to improve the low-voltage-ride-through (LVRT) performance of a two-stage photovoltaic (PV) power plant to deal with grid faults under weak grid condition. Generally, the strength of the grid is closely related to the short circuit ratio (SCR). When the SCR is lower, the strength of the grid is weaker. The PV power plant is composed of an interleaved DC/DC converter and a three-level neutral-point clamped (NPC) inverter. Moreover, the PV power plant possesses the smart inverter function, in which the output active and reactive powers of the inverter are calculated according to the grid codes of the utilities. In order to improve the control performance of the PV power plant to handle grid faults under weak grid condition, an online trained recurrent wavelet fuzzy neural network (RWFNN) is proposed to replace the traditional proportional-integral (PI) controller for the active and reactive powers control of the smart inverter. Furthermore, the proposed controllers of the PV power plant are simulated via PSIM software. In addition, the proposed controllers are implemented by two control platforms using floating-point digital signal processor (DSP). From the simulation and experimental results, excellent control performance for the active and reactive powers control under grid faults and weak grid condition can be achieved by using the intelligent control of the smart inverter.

關鍵字(中)

★ 太陽光發電系統
★ 交錯式直流至直流轉換器
★ 三階層中性點箝位變流器
★ 短路比
★ 弱電網
★ 小波模糊類神經網路

關鍵字(英)

論文目次

中文摘要 I
Abstract II
誌謝 III
目錄 IV
圖目錄 VII
表目錄 XII
第一章緒論 1
1.1 研究背景與動機 1
1.2 文獻回顧 2
1.3 本文貢獻 5
1.4 論文大綱 5
第二章智慧型太陽光發電系統介紹 7
2.1 簡介 7
2.2 太陽能電池特性 7
2.3 三相座標軸轉換 10
2.3.1 靜止座標軸轉換(Clarke轉換) 12
2.3.2 Park轉換 13
2.3.3 變流器之實虛功控制與電流控制 14
2.4 併網型再生能源之低電壓穿越探討 15
2.4.1 故障型態分析 15
2.4.2 正負序成分分析 20
2.4.3 正負序成分偵測 23
2.4.4 二階廣義積分器之鎖相迴路 25
2.4.5 故障電壓偵測與低電壓穿越規範 26
2.5 兩級式電路架構 29
2.5.1 交錯式直流至直流轉換器 29
2.5.2 三階層中性點箝位變流器 32
2.5.3 三階層中性點箝位變流器控制原理 38
第三章弱電網與弱電網穩定性分析 41
3.1 弱電網 41
3.2 弱電網穩定性分析 41
第四章硬體設備與規劃 56
4.1 硬體規劃 56
4.2 數位訊號處理器與周邊電路 57
4.2.1 數位訊號處理器 57
4.2.2 市電電壓偵測電路 58
4.2.3 直流電壓偵測電路 59
4.2.4 電流感測電路 59
4.3 硬體設備 60
4.3.1 可程控直流電源供應器(具太陽能電池陣列模擬功能) 60
4.3.2 三相交流電源供應器 62
4.3.3 饋線阻抗 63
4.3.4 三相變壓器 64
第五章小波模糊類神經網路之太陽光電系統 65
5.1 簡介 65
5.2 小波模糊類神經網路架構 66
5.3 小波模糊類神經網路之線上學習法則 69
5.4 小波模糊類神經網路之收斂性分析 72
5.5 模擬結果 74
第六章遞迴式小波模糊類神經網路之太陽光電系統 77
6.1 簡介 77
6.2 遞迴式小波模糊類神經網路架構 78
6.3 遞迴式小波模糊類神經網路之線上學習法則 81
6.4 遞迴式小波模糊類神經網路之收斂性分析 83
6.5 模擬結果 85
6.6 實作結果 95
第七章結論與未來研究方向 108
7.1 結論 108
7.2 未來研究方向 108
參考文獻 110
作者簡歷 116

參考文獻

[1] 行政院，「積極推動太陽光電」，2019。
[2] 行政院，「前瞻基礎建設計畫―綠能建設」，2019。
[3] 行政院，「太陽光電計畫推動辦理情形」，2019。
[4] S. Liu, P. X. Liu, and X. Wang, “Stability analysis of grid-interfacing inverter control in distribution systems with multiple photovoltaic-based distributed generators,” IEEE Trans. Industrial Electronics, vol. 63, no. 12, pp. 7339–7348, Dec. 2016.
[5] Z. Wang, B. Chen, and J. Wang, “Stochastic DG placement for conservation voltage reduction based on multiple replications procedure,” IEEE Trans. Power Delivery, vol. 30, no. 3, pp. 1039–1047, Jun. 2015.
[6] J. Han, S. Khushalani-Solanki, J. Solanki, and J. Liang, “Adaptive critic design-based dynamic stochastic optimal control design for a microgrid with multiple renewable resources,” IEEE Trans. Smart Grid, vol. 6, no. 6, pp. 2694–2703, Nov. 2015.
[7] S. Liu, P. X. Liu, and X. Wang, “Stochastic small-signal stability analysis of grid-connected photovoltaic systems,” IEEE Trans. Industrial Electronics, vol. 63, no. 2, pp. 1027–1038, Feb. 2016.
[8] G. Fusco and M. Russo, “Robust MIMO design of decentralized voltage controllers of PV systems in distribution networks,” IEEE Trans. Industrial Electronics, vol. 64, no. 6, pp. 4610–4620, Jun. 2017.
[9] S. Mortazavian and Y. A. R. I. Mohamed, “Dynamic analysis and improved LVRT performance of multiple DG units equipped with grid-support functions under unbalanced faults and weak grid conditions,” IEEE Trans. Power Electronics, vol. 33, no. 10, pp. 9017–9032, Oct. 2018.
[10] X. Chen, Y. Zhang, S. Wang, J. Chen, and C. Gong, “Impedance-phased dynamic control method for grid-connected inverters in a weak grid,” IEEE Trans. Power Electronics, vol. 32, no. 1, pp. 274–283, Jan. 2017.
[11] D. Wu, G. Li, M. Javadi, A. M. Malyscheff, M. Hong, and J. N. Jiang, “Assessing impact of renewable energy integration on system strength using site-dependent short circuit ratio,” IEEE Trans. Sustain. Energy, vol. 9, no. 3, pp. 1072–1080, Jul. 2018.
[12] S. M. Alizadeh, C. Ozansoy, and A. Kalam, “Investigation into the impact of PCC parameters on voltage stability in a DFIG wind farm,” in Proc. Australasian Univ. Power Eng. Conf., 2017, pp. 1–6.
[13] L. J. Cai and I. Erlich, “Doubly fed induction generator controller design for the stable operation in weak grids,” IEEE Trans. Sustain. Energy, vol. 6, no. 3, pp. 1078–1084, Jul. 2015.
[14] Q. Jia, G. Yan, Y. Cai, and Y. Li, “Small signal stability analysis of paralleled inverters for multiple photovoltaic generation units connected to weak grid,” in Proc. Int. Conf. Renew. Power Gener. (RPG), Jilin, China, 2017, pp. 1–6.
[15] P. Acuna, L. Moran, M. Rivera, J. Dixon, and J. Rodriguez, “Improved active power filter performance for renewable power generation systems,” IEEE Trans. Power Electron., vol. 29, no. 2, pp. 687-694, Feb. 2014.
[16] R. R. Pereira, C. H. da Silva, L. E. Borges da Silva, G. Lambert-Torres, and J. O. P. Pinto, “New strategies for application of adaptive filters in active power filters,” IEEE Trans. Ind. Appl., vol. 47, no. 3, pp. 1136-1141, May/Jun. 2011.
[17] M. A. Mulla, C. Rajagopalan, and A. Chowdhury, “Compensation of three-phase diode rectifier with capacitive filter working under unbalanced supply conditions using series hybrid active power filter,” IET Power Electron., vol. 7, no. 6, pp. 1566-1577, Jun. 2014.
[18] M. Cirrincione, M. Pucci, G. Vitale, and A. Miraoui, “Current harmonic compensation by a single-phase shunt active power filter controlled by adaptive neural filtering,” IEEE Trans. Ind. Electron., vol. 56, no. 8, pp. 3128-3143, Aug. 2009.
[19] K. Jyotheeswara Reddy and N. Sudhakar, “High voltage gain interleaved boost converter with neural network based MPPT controller for fuel cell based electric vehicle applications,” IEEE Access, vol. 6, pp. 3899-3908, 2018.
[20] S. Dusmez, A. Hasanzadeh, and A. Khaligh, “Comparative analysis of bidirectional three-level dc–dc converter for automotive applications,” IEEE Trans. Ind. Electron., vol. 62, no. 5, pp. 3305-3315, May. 2015.
[21] Y. Chen, C. Tang, and Y. Chen, “PV power system with multi-mode operation and low-voltage ride-through capability,” IEEE Trans. Ind. Electron., vol. 62, no. 12, pp. 7524-7533, Dec. 2015.
[22] S. Y. Chen, Y. H. Hung, and S. S. Gong, “Speed control of vane-type air motor servo system using proportional integral derivative based fuzzy neural network,” Int. J. Fuzzy Syst, vol. 18, no. 6, pp. 553–564, Jan. 2016.
[23] F. J. Lin and R. J. Wai, “Sliding-mode controlled slider-crank mechanism with fuzzy neural network,” IEEE Trans. Ind. Electron., vol. 48, no. 1, pp. 60-70, 2001.
[24] Y. Li, H. L. Wei, and S. A. Billings, “Identification of time-varying systems using multi-wavelet basis functions,” IEEE Trans. Control Syst. Technol., vol. 19, no. 3, pp. 656–663, May 2011.
[25] J. P. S. Catala˜o, H. M. I. Pousinho, and V. M. F. Mendes, “Hybrid wavelet-PSO-ANFIS approach for short-term electricity prices forecasting,” IEEE Trans. Power Syst., vol. 26, no. 1, pp. 137–144, Feb. 2011.
[26] C. H. Lu, “Wavelet fuzzy neural networks for identification and predictive control of dynamic systems,” IEEE Trans. Ind. Electron., vol. 58, no. 7, pp. 3046–3058, Jul. 2011.
[27] M. Shahriari-kahkeshi and F. Sheikholeslam, “Adaptive fuzzy wavelt network for robust fault detection and diagnosis in non-linear systems,” IET Control Theory Appl., vol. 8, no. 15, pp. 1487–1498, Oct. 2014.
[28] S. H. Park and S. I. Han, “Robust-tracking control for robot manipulator with deadzone and friction using backstepping and RFNN controller,” IET Control Theory Appl., vol. 5, no. 12, pp. 1397–1417, Aug. 2011.
[29] F. J. Lin, I. F. Sun, K. J. Yang, and J. K. Chang, “Recurrent fuzzy neural cerebellar model articulation network fault-tolerant control of six-phase permanent magnet synchronous motor position servo drive,” IEEE Trans. Fuzzy Syst., vol. 24, no. 1, pp. 153–167, Feb. 2016.
[30] Y. Y. Lin, J. Y. Chang, and C. T. Lin, “Identification and prediction of dynamic systems using an interactively recurrent self-evolving fuzzy neural network,” IEEE Trans. Neural Netw. Learn. Syst., vol. 24, no. 2, pp. 310–321, Feb. 2013.
[31] T. Mai and Y. Wang, “Adaptive force/motion control system based on recurrent fuzzy wavelet CMAC neural networks for condenser cleaning crawler-type mobile manipulator robot,” IEEE Trans. Control Syst. Technol., vol. 22, no. 5, pp. 1973–1982, Sep. 2014.
[32] S. Ganjefar and M. Tofighi, “Single-hidden-layer fuzzy recurrent wavelet neural network: applications to function approximation and system identification,” Inf. Sci., vol. 294, pp. 269–285, Feb. 2015.
[33] 楊柏輝，「應用單級轉換器之太陽能光電系統實虛功控制策略」，國立中央大學，碩士論文，2016年六月。
[34] K. Ishaque, Z. Salam, M. Amjad, and S. Mekhilef, “An improved particle swarm optimization (PSO)-based MPPT for PV with reduced steady-state oscillation,” IEEE Trans. Power Electron., vol. 27, no. 8, pp. 3627-3638, Aug. 2012.
[35] 黃仲欽，「交流電動機控制」，交流電動機課程講義，民國97 年。
[36] 柯廷翰，「考慮配電系統三相故障之具低電壓穿越能力之智慧型太陽光電系統」，國立中央大學，碩士論文，2013年六月。
[37] G. Saccomando, J. Svensson, and A. Sannino, “Improving voltage disturbance rejection for variable-speed wind turbines,” IEEE Trans. Energy Convers., vol. 17, no. 3, pp. 422-428, Sep. 2002.
[38] A. Nicastri and A. Nagliero, “Comparison and evaluation of the PLL techniques for the design of the grid-connected inverter systems,” IEEE International Symposium on Industrial Electronics, pp. 3865-3870, 2010.
[39] 李軒宇，「具低電壓穿越能力之單級智慧型太陽能光電系統」，國立中央大學，碩士論文，2014年六月。
[40] Grid Code High and Extra High Voltage, E.ON Netz GmbH, Bayreuth, Germany, Apr. 2006. [Online]. Available: http://www.nationalgrid.com/uk
[41] 賴煜凱，「應用於三相不平衡負載電流補償之智慧型太陽光電發電系統」，國立中央大學，碩士論文，2018年六月。
[42] J. Sun, “Dynamics and Control of Switched Electronic Systems,” Springer, ch. 2, sec. 3, pp. 48-53, 2012.
[43] 蔡居甫，「應用於儲能系統之智慧型風場功率平滑化之控制」，國立中央大學，碩士論文，2015年六月。
[44] 使用手冊，「可程控直流電源供應器(具太陽能電池陣列模擬) 62000H系列使用手冊」，Chroma，2012。
[45] User Manual, User’s Manual PCR-LE series, KIKUSUI, Feb. 2013.
[46] 俞韋安，「應用於內藏式永磁同步馬達之智慧型最佳伺服頻寬調整及慣量估測」，中央大學電機工程系，碩士論文，民國107年7月。
[47] F. J. Lin, R. J. Wai, and P. K. Huang, “Two-axis motion control system using wavelet neural network for ultrasonic motor drives,”IEE Proc. Electr. Power Appl., vol. 151, no. 5, pp. 613-621, Sep. 2004.
[48] J. Zhang, G. G. Walter, Y. Miao, and W. N. W. Lee, “Wavelet neural networks for function learning,” IEEE Trans. Signal Process., vol. 43,no. 6, pp. 1485-1497, Jun. 1995.
[49] S. J. Yoo, Y. H. Choi, and J. B. Park, “Generalized predictive control based onself-recurrent wavelet neural network for stable path tracking of mobile robots:Adaptive learning rates approach,” IEEE Trans. Circuits Syst. I: Reg. Papers, vol. 53,no. 6, pp. 1381-1395, Jun. 2006.
[50] 陳朝順，「微電網系統暫態減緩之智慧型控制技術建立」，義守大學電機工程系，行政院原子能委員會委託研究計劃研究報告，民國101年12月。
[51] F. J. Lin, K. C. Lu, T. H. Ke, B. H. Yang, and Y. R. Chang, “Reactive power control of three-phase grid-connected PV system during grid faults using takagi–sugeno–kang probabilistic fuzzy neural network nontrol,” IEEE Trans. Ind. Electron., vol. 62, no. 9, pp. 5516–5528, Sep. 2015.

指導教授

林法正(Faa-Jeng Lin)

審核日期

2019-8-1

推文