參考文獻 |
[1] EPIA, “Global market outlook for solar power 2015-2019”, Jan. 2016.
[2] 經濟部能源局,2012年能源產業技術白皮書,經濟部能源局,台北市,2012。
[3] 經濟部能源局,綠色能源產業躍升計畫,2009。
[4] 經濟部能源局,「陽光屋頂百萬座」計畫,2011。
[5] 台灣電力公司,http://www.taipower.com.tw。
[6] F. Blaabjerg, R. Teodorescu, M. Liserre, and A. V. Timbus, “Overview of control and grid synchronization for distributed power generation systems,” IEEE Trans. Ind. Electron., vol. 53, no. 5, pp. 1398-1409, Oct. 2006.
[7] A. Jamehbozorg, S. N. Keshmiri, and G. Radman, “PV output power smoothing using energy capacitor system,” in Proc. IEEE Conf. Southeastcon, Nashville, TN, USA, pp. 24-29, 2011.
[8] G. Wang, G. Konstantinou, C. D. Townsend, J. Pou, S. Vazquez, G. D. Demetriades, and V. G. Agelidis, “A review of power electronics for grid connection of utility-scale battery energy storage systems,” IEEE Trans. Sustain. Energy, vol. 7, no. 4, pp. 1778-1790, 2016.
[9] M. Lave, J. Kleissl, A. Ellis, and F.Mejia, “Simulated PV power plant variability: Impact of utility-imposed ramp limitations in Puerto Rico,” in Proc. IEEE Conf. Photovoltaic Specialists Conference, pp. 1817-1821, 2013.
[10] M. Jannati, S. H. Hosseinian, B. Vahidi and G. J. Li, “Mitigation of windfarm power fluctuation by adaptive linear neuron-based power tracking method with flexible learning rate,” IET Renew. Power Gener., vol. 8, no. 6, pp. 659-669, 2014.
[11] A. Esmaili, and A. Nasiri, “Power smoothing and power ramp control for wind energy using energy storage,” in Proc. IEEE Conf. Energy Conversion Congress and Exposition, pp. 922-927, 2011.
[12] M. E. Amiryar, and K. R. Pullen, “A review of flywheel energy storage system technologies and their applications,” Appl. Sci., vol. 7, 2017.
[13] T. Asao, T. Murata, J. Tamura, M. Kubo, A. Kuwayama, and T. Matsumoto, “Smoothing control of wind power generator output by superconducting magnetic energy storage system,” in Proc. IEEE Conf. Electrical Machines and Systems, pp. 302-307, 2007.
[14] H. X. Jia, Y. Zhang, and Y. F. Wang, “Application of energy storage technology in wind power systems,” Renew. Energy, no.27, pp. 10-15, 2009.
[15] G. Wang, M. Ciobotaru, and V. G. Agelidis, “Power smoothing of large solar PV plant using hybrid energy storage,” IEEE Trans. Sustain. Energy, vol. 5, no. 3, pp. 834-842, 2014.
[16] J. Johnson, A. Ellis, A. Denda, K. Morino, T. Shinji, T. Ogata, and M. Tadokoro, “PV output smoothing using a battery and natural gas engine-generator,” in Proc. IEEE Conf. Photovoltaic Specialists Conference, pp. 1811-1816, 2013.
[17] X. Li, D. Hui, and X. Lai, “Battery energy storage station (BESS)-based smoothing control of photovoltaic (PV) and wind power generation fluctuations,” IEEE Trans. Sustain. Energy, vol. 4, no. 2, pp. 464-473, 2013.
[18] A. Saez-de-Ibarra, E. Martinez-Laserna, D. Stroe, M. Swierczynski, and P. Rodriguez, “Sizing study of second life Li-ion batteries for enhancing renewable energy grid integration,” IEEE Trans Ind. Appl., vol. 52, no. 6, pp. 4999-5008, 2016.
[19] W. Y. Chang, “The state of charge estimating methods for battery: A Review,” Appl. Math., vol. 2013, no. 1, pp. 1-7, 2013.
[20] C. Zhang, L. Y. Wang, X. Li, W. Chen, G. G. Yin, and J. Jiang, “Robust and adaptive estimation of state of charge for Lithium-ion batteries,” IEEE Trans. Ind. Electron., vol. 62, no. 8, pp. 4948-4957, 2015.
[21] M. Coleman, C. K. Lee, C. Zhu, and W. G. Hurley, “State-of-charge determination from EMF voltage estimation: using impedance, terminal voltage, and current for Lead-acid and Lithium-ion batteries,” IEEE Trans. Ind. Electron., vol. 54, no. 5, pp. 2550-2557, 2007.
[22] G. Dong, J. Wei, C. Zhang, and Z. Chen, “Online state of charge estimation and open circuit voltage hysteresis modeling of LiFePO4 battery using invariant imbedding method,” Appl. Energy, vol. 162, pp. 163-171, 2016.
[23] Z. Liu, D. W. Gao, Y. H. Wan, and E. Muljadi, “Wind power plant prediction by using neural networks,” 2012 IEEE Energy Conversion Congress and Exposition (ECCE), pp.3154-3160, 2012.
[24] F. J. Lin, K. H. Tan, and C. H. Tsai, “Improved differential evolution-based Elman neural network controller for squirrel-cage induction generator system,” IET Renew. Power Gener., vol. 10, no. 7, pp. 988-1001, 2016.
[25] M. E. G. Urias, E. N. Sanchez, and L. J. Ricalde, “Improved differential evolution-based Elman neural network controller for squirrel-cage induction generator system,” IEEE System Journal, vol. 9, no. 3, pp. 945-953, 2014.
[26] W. Yu, and X. Li, “Fuzzy identification using fuzzy neural networks with stable learning algorithms,” IEEE Trans. Fuzzy Sys., vol. 12, no. 3, pp. 411-420, 2004.
[27] F. J. Lin, L. T. Teng, P. H. Shieh, and Y. F. Li, “Intelligent controlled-wind-turbine emulator and induction-generator system using RBFN,” IET Electr. Power Appl., vol. 153, no. 4, pp. 608-618, Jul. 2006.
[28] F. J. Lin, M. S. Huang, P. Y. Yeh, H. C. Tsai, and C. H. Kuan, “DSP-based probabilistic fuzzy neural network control for Li-ion battery charger,” IEEE Trans. Power Electron., vol. 27, no. 8, pp. 3782-3794, Aug. 2012.
[29] W. M. Lin and C. M. Hong, “A new Elman neural network-based control algorithm for adjustable-pitch variable-speed wind-energy conversion systems,” IEEE Trans. Power Electron., vol. 26, no. 2, pp. 473-481, Feb. 2011.
[30] D. F. Specht, “Probabilistic neural network,” Neural Networks, vol. 3, no. 1, pp. 109-118, 1990.
[31] H. X. Li and Z. Liu, “A probabilistic neural-fuzzy learning system for stochastic modeling,” IEEE Trans. Fuzzy Sys., vol. 16, no. 4, pp. 898-908, Aug. 2008.
[32] N. Sozhamadevi, R. S. L. Delcause, and Dr. S. Sathiyamoorthy, “Design and implementation of probabilistic fuzzy logic control system,” in Proc. IEEE Conf. Emerging Trends in Science, Engineering and Technology, pp. 523-531, 2012.
[33] K. H. Cheng, C. F. Hsu, C. M. Lin, T. T. Lee, and C. Li, “Fuzzy neural sliding mode control for dc-dc converters using asymmetric gaussian membership functions,” IEEE Trans. Ind. Electron., vol. 54, no. 3, pp. 1528-1536, 2004.
[34] C. H. Lee, T. W. Hu, C. T. Lee, and Y. C. Lee, “A recurrent interval type-2 fuzzy neural network with asymmetric membership functions for nonlinear system identification,” in Proc. IEEE Conf. Fuzzy System, pp. 1496-1502, 2008.
[35] 杜冠賢,陳耀銘,吳財福,姜士凱,鋰離子電池充電器研製,第六屆台灣電力電子研討會,2007。
[36] 蔡瀚章,智慧型控制數位化鋰錳電池充電器之研製,碩士論文,國立中央大學電機工程學系,桃園,2011。
[37] 華志強、江錫津、薛宗偉,鋰鐵電池與鉛酸電池充放電特性,第八屆臺灣電力電子研討會暨展覽會,2009年9月,第711-715頁。
[38] G. P. Hancke, “A fiber-optic density sensor for monitoring the state-of-charge of a Lead-acid battery,” IEEE Trans. Instrum. Meas., vol. 39, no. 1, pp. 247-250, Feb. 1990.
[39] D. K. Khatod, V. Pant, and J. Sharma, “Analytical approach for wellbeing assessment of small autonomous power systems with solar and wind energy sources,” IEEE Trans. Energy Convers., vol. 25, no. 2, pp. 535-545, 2010.
[40] I. Parra, M. Muñoz, E. Lorenzo, M. García, J. Marcos, and F. Martínez-Moreno, “PV performance modelling: A review in the light of quality assurance for large PV plants,” Renewable and Sustainable Energy Reviews, vol. 78, pp. 780-797, 2017.
[41] IEC 61724, Photovoltaic system performance monitoring Guidelines for measurement, data exchange and analysis, 1998.
[42] 黃仲欽,交流電動機控制,交流電動機課程講義,民國97年。
[43] R. Yan and T. K. Saha, “Investigation of voltage stability for residential customers due to high photovoltaic penetration,” IEEE Trans. Power Syst., vol. 27, no. 2, pp. 651-661, May 2012.
[44] N. Mohan, T. M. Undeland, and W. P. Robbins, Power electronics, 1989.
[45] XPS2E-025020CB Datasheet, LiFeTech Energy Co.
[46] 呂宗翰,智慧型控制雙饋式感應風力發電系統之研製,國立中央大學,碩士論文,2010年六月。
[47] M.R.I. Sheikh, S.M. Muyeen, R. Takahashi, T. Murata and J. Tamura, “Minimization of fluctuations of output power and terminal voltage of wind generator by using STATCOM/SMES,” in Proc. IEEE Conf. PowerTech, Bucharest, pp. 1-6, 2008.
[48] Q. Jiang, Y. Gong and H. Wang, “A battery energy storage system Dual-layer control strategy for mitigating wind farm fluctuations,” IEEE Trans. Power Syst., vol. 28, no. 3, pp. 3263-3273, 2013.
[49] F. J. Lin, H. C. Chiang, J. K. Chang, and Y. R. Chang, “Intelligent wind power smoothing control with BESS,” IET Renew. Power Gener., vol. 11, no. 2, pp. 398-407, Oct. 2016
[50] The University of Queensland. UQ SOLAR Photovoltaic Live Data [Online]. Available: http://solar.uq.edu.au/user/reportPower.php.
[51] M. Jannati, S. H. Hosseinian, B. Vahidi, and G. J. Li, “Mitigation of windfarm power fluctuation by adaptive linear neuron-based power tracking method with flexible learning rate,” IET Renew. Power Gener., vol. 8, no. 6, pp. 659-669, 2014. |