由於風力發電機輸出不穩定主要原因在於風速發生變化，風力發電機輸出也跟著變化，而影響風速的因素包括地形、溫度、濕度等。因此，風力發電預測是一種非常複雜、多維度且高度非線性的系統。類神經網路技術的優點在於能學習輸入與輸出間的關係而不需要提供轉換的數學函式，可完成複雜的非線性映射、聯想、資料分類、知識處理等工作，且類神經網路具有並行處理能力可減少運算時間，故適合應用於數量眾多風機組之發電量預測。
本論文的目的在於應用類神經網路技術於預測長時間之風力發電量，並分析金門風場之風力發電量預測效果。最後，利用MATLAB實現一類神經網路結合氣象資料之風力發電預測系統，具有領前時間1~48小時之風力發電預測能力。

The wind turbine systems are unstable power sources. The main reason is that their power outputs heavily depend on wind speed. However, terrain, temperature, humidity and other factors affect wind speed. Therefore, wind power forecasting is a very complex, multi-dimensional, and highly nonlinear system. Neural network has the ability to learn the relationship between system input and output, and performs complex non-linear mapping, data classification, knowledge processing, and so forth. In addition, because neural network has the ability of parallel processing, computation time can be reduced. Therefore, it is very suitable for wind power forecasting.
The purpose of this thesis is to use neural network technology to design a wind power forecasting system. Moreover, the efficiency of the proposed wind power forecasting system in Kinmen farm is described. Finally, we use MATLAB to implement the proposed wind power forecasting system with 48-hours ahead in Kinmen farm.

[1] 台灣電力公司網站。取自http://www.taipower.com.tw/content/new_info/new_info-b31.aspx?LinkID=8
[2] 呂藝光，類神經網路結合氣象資料於長領前時間之風力發電預測分析試驗，台電委託試驗結案報告，2013。
[3] Alexiadis, M.C., P.S. Dokopoulos, H.S. Sahsamanoglou, and I.M. Manousaridis, “Short-Term Forecasting of Wind Speed and Related Electrical Power,” Solar Energy 63, pp. 61-68, 1998.
[4] S.H. Jangamshetti and V.G. Rau, “Site matching of wind turbine generators: A case study,” IEEE Trans. Energy Conversion, pp. 1537-1543, 1999.
[5] S.H. Jangamshetti and V.G. Rau, “Optimum siting of wind turbine generators,” IEEE Trans. Energy Conversion, vol. 16, no. 1, pp. 8-13, 2001.
[6] S.H. Jangamshetti and V.G. Rau, “Normalized power curves as a tool for identification of optimum wind turbine generator parameters,” IEEE Trans. Energy Conversion, vol. 16, no. 3, pp. 283-288, 2001.
[7] C. Kwan and F. L. Lewis, “Robust backstepping control of nonlinear systems using neural networks,” IEEE Transactions Syst., vol. 30, pp. 753–765, 2000.
[8] S. Mathew, K. P. Pandey, and A. Kumar, “Analysis of wind regimes for energy estimation,” Renewable Energy, vol.25, pp. 381-399, 2002.

[9] Moreno, P., L. Benito, R. Borén, and M. Cabré, “Short-Term Wind Forecast. Results of First Year Planning Maintenance at a Wind Farm,” European Wind Energy Conference and Exhibition, Madrid (ES), 2003.
[10] Potter, C.W. and M. Negnevitsky, “Very Short-Term Wind Forecasting for Tasmanian Power Generation,” IEEE Trans. Power Systems, pp. 965-972, 2006.
[11] S.Y. Hu and J.H. Cheng, “Performance evaluation of pairing between sites and wind turbines,” Renewable Energy, vol. 32, pp. 1934-1947, 2007.
[12] G. Sideratos and N. D. Hatziargyrious, “An advanced statistical method for wind power forecasting,” IEEE Trans. Power Systems, vol. 22, no. 1, pp. 258-265, 2007.
[13] Chen Ye, Gengyin Li, and Ming Zhou,” A combined prediction method of wind farm power,” Critical Infrastructure (CRIS), 2010 5th International Conference, 2010.
[14] Y. Liu, X.F. Lu, R.M. Fang, and Y.B. Song, “A review on wind speed forecast methods in wind power system,” Power system and clean energy, vol.26 no. 6, 2010.
[15] Giebel G., Kariniotakis G., and Brownsword R., The State-Of-The-Art in Short-Term Prediction of Wind Power: A Literature Overview, 2nd edition ANEMOS.plus. 2011
[16] Khalid, M. and Savkin, A.V., “A Method for Short-Term Wind Power Prediction With Multiple Observation Points,” IEEE Transactions Power Systems, vol.27, 2012.
[17] 千架海陸風力機網站。取自http://wind.itri.org.tw/index.aspx
[18] 台灣風力發電產業協會網站。取自http://www.twtia.org.tw/index.aspx
[19] 吳天明，台電在台灣本島及離島推動風力發電概況報導，源雜誌，2012。
[20] 黃思倫，風力發電場的串聯限流電抗器之研究，逢甲大學資訊電機工程碩士在職專班碩士論文，台中，2008。
[21] J.L.Deng, “Control problems of grey systems,” Systems and Control Letters, vol. 1, pp. 288-294, 1982.
[22] J.L.Deng, “Introduction to grey system theory,” The Journal of Grey System, vol. 1, no. 1, pp. 1-24, 1989.
[23] J. F. Walker and N. Jenkins, Wind energy, Chicester, UK: John Wiley &Sons Ltd., 1997.
[24] S. Heier, Orid integration of Wind Energy Conversion System, Chicester, UK: John Wiley &Sons Ltd., 1997.
[25] 溫坤禮，趙忠賢，張宏志，陳曉瑩，溫惠筑，灰色理論，五南圖書公司，2009。
[26] T.H.M., E.F. El-Saadany, and M.M.A. Salama, “Grey Predictor for Wind Energy Conversion Systems Output Power Prediction,” IEEE Trans Power Systems, vol. 21, no. 3, pp. 1450-1452, 2006.
[27] T.H.M. El-Fouly, E.F. El-Saadany, and M.M.A. Salama, “Improved Grey predictor rolling models for wind power prediction,” Generation, Transmission & Distribution, IET, vol. 1, pp. 928-937, 2007.
[28] Shi Nan, Zhou Su-quan, Zhu Xian-hui, Su Xun-wen, and Zhao Xiao-yan, “Wind speed forecasting based on grey predictor and genetic neural network models,” Measurement, Information and Control (ICMIC), International Conference, vol. 2, 2013.

[29] Liu Jian-Yong, Li Ling, Zhang Yong-Li, and Li Yan, ” A multi-series grey forecasting model based on neural network improved by genetic algorithm,” Grey Systems and Intelligent Services, IEEE International Conference, pp. 684-688, 2007.
[30] 葉怡成，類神經網路-模式應用與實作，儒林圖書公司，2000 。
[31] 蘇木春，張孝德，機器學習：類神經網路、模糊系統以及基因演算法則，全華圖書公司，2004。
[32] 羅華強，類神經網路：MATLAB應用，高立圖書公司，2005。
[33] Gencay Ramazan, “Non-linear prediction of security returns with moving average rules,” Joural of Forecasting, vol.15, p 165-174, 1996.
[34] 吳繼平，應用類神經網路及基因演算法預測風速與風力發電量，中原大學電機工程研究所碩士論文，中壢，2007。
[35] 張仁恭，應用神經網路於風力發電量預測之研究，聖約翰科技大學電機工程系碩士論文，淡水，2011。
[36] Shuhui Li, Donald C. Wunsch, Edgar A. O’Hair, and Michael G. Giesslmann, “Using neural networks to estimate wind turbine power generation,” IEEE Trans. Energy Conversion, vol. 16, no. 3, pp. 276-282, 2001.
[37] Jiali Shuai and Jixian Qu, “The study of three kinds of wind power prediction methods,” Power Engineering and Automation Conference (PEAM), 2012.
[38] R. A. Johnson and D. W. Wichern, Applied Multivariate Statistical Analysis, 6th ed., Pearson Education, 2007.
[39] 林震岩，多變量分析-SPSS的操作與應用，智勝文化事業有限公司， 2007。