本文所提之預測方法乃是透過短期負載預測中供電饋線與每日逐時氣象資訊之關聯，對影響負載的關鍵因素進行分析，進而提出一套基於氣象資料的短期配電饋線負載預測方法，以準確預估未來各時間點之負載容量。本文以饋線的歷史資料，將供電饋線逐日逐時負載區分成數個不同類型，包括工作日、週末日、節慶假日等3大類型。每日逐時氣象資訊包括氣壓(hPa)、溫度(℃)、相對濕度(%)、風速(m/s)、風向(各方位)、降水量(mm) 等因素。依據所分類之負載類型，一一進行影響負載變化之可能因素的相關性分析，使可達最佳之負載預測。最後，本文以實際負載資料，驗證本文所提系統之可行性。

This study presents a short-term load forecasting system of distribution feeders considering weather information. Sensitivity analysis of the key weather factors influencing the load is firstly conducted. Then , this study proposed an electrical power supply feeder load forecasting technique to accurately estimate load capacity in various time of the future. The historical load data of the feeder use in the study are divided into three categories, workday, weekend, and holiday. The hourly weather information adopted for load forecasting include the atmospheric pressure (hPa), the temperature (℃), the relative humidity (%), the wind speed (m/s), the wind direction (every position), #and the precipitation (mm). According to different kinds of load types together with the weather informations relevance analysis of possible factors influencing the load variation is performed to make the optimized load forecast. Finally, the feasibility of the system proposed by the study has been proven by the actual historical loading data.

參考文獻
[1] A.P.A. da Silva and L.S. Moulin, “Confidence Intervals for Neural Network Based Short-term Load Forecasting,” IEEE Trans on Power Systems, Volume 15, Issue 4, Nov. 2000 Page(s):1191 – 1196.
[2] J.W. Taylor and R. Buizza, “Neural Network Load Forecasting with Weather Ensemble Predictions, ” IEEE Transactions on Power Systems, Volume 17, Issue 3, Aug. 2002 Page(s):626 – 632.
[3] A. Khotanzad , R. Afkhami-Rohani and D. Maratukulam, “ANNSTLF-Artificial Neural Network Short-Term Load Forecaster Generation Three,” IEEE Transactions on Power Systems, Volume 13, Issue 4, Nov. 1998 Page(s):1413 – 1422.
[4] S.J. Kiartzis, C.E. Zoumas, J.B. Theocharis, A.G. Bakirtzis and V. Petridis, “ Short-Term Load Forecasting in an Autonomous Power System Using Artificial Neural Networks, ” IEEE Transactions on Power Systems, Volume 12, Issue 4, Nov. 1997 Page(s):1591 – 1596.
[5] D.C. Park, M.A. El-Sharkawi, II R.J. Marks, L.E. Atlas and M.J. Damborg, “Electric load forecasting using an artificial neural network, ” IEEE Transactions on Power Systems, Volume 6, Issue 2, May 1991 Page(s):442 – 449.
[6] M. Mangeas and C. Muller, “ An Automatic Search of Feedforward Neural Network Architecture Based on Genetic Algorithms: Application to the Short-term Load Forecasting, ”Proceeding of International Conference on Intelligent System Application to Power Systems, 1997:362-366.
[7] M.H. Choueiki, C.A. Mount-Campbell and S.C. Ahalt, “ Building a Quasi Optimal Neural Network to Solve the Short-Term Load Forecasting Problem, ” IEEE Transactions on Power Systems, Volume 12, Issue 4, Nov. 1997 Page(s):1432 – 1439.
[8] P.K. Dash, H.P. Satpathy, A.C. Liew and S. Rahman, “A Real-Time Short-Term Load Forecasting System Using Functional Link Network, ”IEEE Transactions on Power Systems, Volume 12, Issue 2, May 1997 Page(s):675 – 680.
[9] H.S. Hippert, C.E. Pedreira and R.C. Souza, “Hippert H S, Pedreira C E, Souza R C. Neural Networks for Short-Term Load Forecasting: A Review and Evaluation, ”IEEE Transactions on Power Systems, Volume 16, Issue 1, Feb 2001 Page(s):44 – 55.
[10] T.M. Peng, N.F. Hubele and G.G. Karady, “Advancement in the Application of Neural Networks for Short-Term Load Forecasting, ” IEEE Transactions on Power Systems, Volume 7, Issue 1, Feb. 1992 Page(s):250 – 257.
[11] T. Matsui, T. Iizaka and Y. Fukuyama , “Peak Load Forecasting Using Analyzable Structured Neural Network, ” IEEE PES 2001 Winter Meeting, 2001. Volume 2, 28 Jan.-1 Feb. 2001 Page(s):405 - 410 .
[12] K.Y.Lee, Y.T. Cha and J.H. Park , “Short-term Load Forecasting Using an Artificial Neural Network, ”IEEE Transactions on Power Systems, 1992,7(1): 124-132. Volume 7, Issue 1, Feb. 1992 Page(s):124 - 132
[13] A.D. Papalexopoulos, Shangyou Hao and Tie-Mao Peng, “An Implementation of a Neural Network Based Load Forecasting Model for the EMS, ” IEEE Transactions on Power Systems, Volume 9, Issue 4, Nov. 1994 Page(s):1956 – 1962.
[14] R. Lamedica, A. Prudenzi, M. Sforna, M. Caciotta and V.O. Cencellli, “ A Neural Network Based Technique for Short-Term Forecasting of Anomalous Load Periods, ” IEEE Transactions on Power Systems, Volume 11, Issue 4, Nov. 1996 Page(s):1749 – 1756.
[15] Darbellay G A and M. Slama, “Forecasting the Short-Term Demand for Electricity Do Neural Networks Stand a Better Chance, ”Int. J. Forecast, 2000,voI.16:71-83.
[16] A.S. AlFuhaid, M.A. El-Sayed and M.S. Mahmoud, “A1Fubaid A S, El-Sayed M A, Mahmoud M S. Cascaded Artificial Neural Networks for Short-Term Load Forecasting, ” IEEE Transactions on Power Systems, Volume 12, Issue 4, Nov. 1997 Page(s):1524 – 1529.
[17] K.L. Ho, Y.-Y. Hsu and C.-C. Yang , “Short term load forecasting using a multilayer neural network with an adaptive learning algorithm, ” IEEE Transactions on Power Systems, Volume 7, Issue 1, Feb. 1992 Page(s):141 – 149.
[18] S.-T. Chen, D.C. Yu and A.R. Moghaddamjo , “Weather Sensitive Short-Term Load Forecasting Using Nonfully Connected Artificial Neural Network, ”IEEE Transactions on Power Systems, Volume 7, Issue 3, Aug. 1992 Page(s):1098 – 1105.
[19] T. Senjyu, H. Takara, K. Uezato and T. Funabashi , “One-Hour-Ahead Load Forecasting Using Neural Network , ”IEEE Transactions on Power Systems, Volume 17, Issue 1, Feb. 2002 Page(s):113 – 118.
[20] J. Vermaak and E.C. Botha , “Recurrent Neural Networks for Short-term Load Forecasting, ”IEEE Transactions on Power Systems, Volume 13, Issue 1, Feb. 1998 Page(s):126 – 132.
[21] D.Srinivasan, Swee Sien Tan, C.S. Cheng and Eng Kiat Chan , “Parallel neural network-fuzzy expert system strategy for short-term load forecasting: system implementation and performance evaluation, ”IEEE Transactions on Power Systems, Volume 14, Issue 3, Aug. 1999 Page(s):1100 – 1106.
[22] D. Srinivasan, A.C. Liew and C.S. Chang , “ Forecasting Daily Load Curves Using a Hybrid Fuzzy-Neural Approach, ” IEE Proceedings-Generation Transmission and Distribution, Volume 141, Issue 6, Nov. 1994 Page(s):561 – 567.
[23] O. Mohammed, D. Park, R. Merchant, T. Dinh, C. Tong, A. Azeem, J. Farah and C. Drake , “Practical Experiences with an Adaptive Neural Network Short-Term Load Forecasting System, ” IEEE Transactions on Power Systems, Volume 10, Issue 1, Feb. 1995 Page(s):254 – 265.
[24] I. Drezga and S. Rahman, “Input Variable Selection for ANN-Based Short-Term Load Forecasting, ”IEEE Transactions on Power Systems, Volume 13, Issue 4, Nov. 1998 Page(s):1238 – 1244.
[25] I. Drezga and S. Rahman, “Short-Term Load Forecasting with Local ANN Predictors, ” IEEE Transactions on Power Systems, Volume 14, Issue 3, Aug. 1999 Page(s):844 – 850.
[26] J T. Connor, “A Robust Neural Network Filter for Electricity Demand Prediction, ”J Forecas4 1996, 15 (6):437-458.
[27] J S McMenamin and F A. Monforte , “Short-Term Energy Forecasting with Neural Networks, ”Energy J, 1998, 19 (4): 43-61.
[28] M.H. Choueiki, C.A. Mount-Campbell and S.C. Ahalt , “Implementing a Weighted Least Squares Procedure in Training a Neural Network to Solve the Short-Term Load Forecasting Problem, ” IEEE Transactions on Power Systems, Volume 12, Issue 4, Nov. 1997 Page(s):1689 – 1694.
[29] J T. Connor, “ A Robust Neural Network Filter for Electricity Demand Prediction, ” J Forecas~ 1996, 15 (6):437-458.
[30] T.W.S. Chow and C.T. Leung , “Neural Network Based Short-Term Load Forecasting Using Weather Compensation, ” IEEE Transactions on Power Systems, Volume 11, Issue 4, Nov. 1996 Page(s):1736 – 1742.
[31] R. Lamedica, A. Prudenzi, M. Sforna, M. Caciotta and V.O. Cencellli , “ A Neural Network Based Technique for Short-Term Forecasting of Anomalous Load Periods, ”IEEE Transactions on Power Systems, Volume 11, Issue 4, Nov. 1996 Page(s):1749 – 1756.
[32] A. Khotanzad, Rey-Chue Hwang, A. Abaye and D. Maratukulam, “ An Adaptive Modular Artificial Neural Network Hourly Load Forecaster and Its Implementation at Electric Utilities, ” IEEE Transactions on Power Systems, Volume 10, Issue 3, Aug. 1995 Page(s):1716 – 1722.
[33] A. Khotanzad, R. Afkhami-Rohani, Tsun-Liang Lu, A. Abaye, M. Davis and D.J. Maratukulam, “ANNSTLF-a neural-network-based electric load forecasting system, ” IEEE T. Neural Nets, Volume 8, Issue 4, July 1997 Page(s):835 – 846.
[34] 台電公司配電技術手冊（一）規劃設計篇，2009年。
[35] 台電公司配電技術手冊（三）運轉維護篇，2009年。
[36] 台電公司業務處「配電系統負載預測編製程序與方法整理報告」，2008年。
[37] 台電公司業務處「負載預測及改壓」，2005年。
[38] 台電公司「電力系統概要」，2008年。
[39] 台電公司「負載預測與短期電源運用」，2009年。
[40] 鄒譓隆，「使用MATLAB程式輔助排定變電所停電轉供表格之研究-以臺電臺北北區營業處淡水變電所為例」，國立台灣大學，2007年。
[41] 李建鋒，「運用脈衝電流法於模鑄式比流器之加速老化研究」碩士論文，國立台灣科技大學，2007年。
[42] 羅華強，「類神經網路--MATLAB的應用」，高立圖書有限公司，第2版，2005年7月。
[43] 葉怡成，「類神經網路模式應用與實作」，儒林圖書，第五版，1997年10月。
[44] 施柏屹，「倒傳遞類神經網路學習收斂之初步探討」，國立中央大學機械工程研究所，2000年。
[45] 葉怡成，「應用類神經網路」，儒林圖書，第三版，2002年6月。
[46] 焦成李，「神經網路系統理論」，儒林圖書，1991年。
[47] 沈宗澤，「以遺傳演算法及共軛梯度法訓練類神經網路」，碩士論文，國立成功大學，2001年。
[48] C.-N. Lu, H.-T. Wu and S. Vemuri , “Neural Network Based Short Term Load Forecasting, ” IEEE Transactions on Power Systems, Volume 8, Issue 1, Feb. 1993 Page(s):336 – 342.