03790nas a2200445 a 4500 20260818155749.0 130314s2011 th uu|m rtt 0| a1eng d .b12116166 AIT Thesis no.ET-11-24 Chonlapat Leewarinpanich Monthly electricity demand forecast for Provincial Electricity Authority using autoregressive integreted moving average (ARIMA) and artificial neural network (ANN): a case study of Chiangmai Pathum Thani, Thailand : Asian Institute of Technology, 2011 66 leaves : ill. + 1 online resource Thesis ; no. ET-11-24 A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science in Energy Thesis (M.Sc.) - Asian Institute of Technology, 2011 This study analyzes and forecasts monthly electricity demand for Provincial Electricity Authority in Chingmai with two approaches. They are Autoregressive Integrated Moving Average (ARIMA) and Artificial Neural Network (ANN). The study focuses on monthly historical data of electricity consumption from 2003 to 2010. ARIMA method used in the study will use SPSS software. Artificial Neural Network (ANN) approach applied the multi - layer perceptron and backpropagation algorithm and MATLAB program has been used for the study. This study involves not only past electricity consumption pattern, but also local socio - economic and climatic factors influencing electricity demand in the model such as monthly average temperature, monthly average maximum temperature, monthly average minimum temperature, number of customers and Ft charge. According to the study, various error measures (MPE, MAPE, MAE and RMSE) are used to evaluate the model performance. All of the error measures confirm that forecasted consumption results from ANN are closer to the actual data than forecasted demand from ARIMA. The MPE, MAPE, MAE and RMSE of testing data from ARIMA model are - 2.42%, 4.53%, 9.16 and 12.28, respectively. The MPE, MAPE, MAE and RMSE of testing data from ANN model are - 0.21%, 1.91%, 3.58 and 4.68, respectively. Therefore, ANN is an attractive technique applied for electricity demand forecast in Chiangmai. Electric power consumptionr Thailand Chiang Mai Marpaung, Charles O.P., Chairperson Weerakorn Ongsakul, Examination Committee Singh, Jai Govind, Examination Committee PEA, Scholarship donor Asian Institute of Technology Education Cooperation Project, Scholarship donor Royal Thai Government Fellowship, Scholarship donor Asian Institute of Technology. Thesis ; no. ET-11-24 Full-Text http://203.159.5.9/ait-thesis/detail.php?q=B02253 .b12116166 mnait z 240403 0 130314 m a z 0 000:001:PDF:b1211616:000897:0:0:0:0:0:0 Abstract n mnait mnait mnarc 20 40 Barcode : 30050120602486 CREATED : 2013-03-15 RECORD # : i12726874 LPATRON : 0 LCHKIN : - # RENEWALS : 0 # OVERDUE : 0 IUSE3 : 0 TOT CHKOUT : 0 TOT RENEW : 0 Barcode : 30050120602494 CREATED : 2013-03-15 RECORD # : i12726886 LPATRON : 0 LCHKIN : - # RENEWALS : 0 # OVERDUE : 0 IUSE3 : 2 TOT CHKOUT : 0 TOT RENEW : 0 Barcode : 30050120368088 CREATED : 2016-08-06 RECORD # : i13023263 LPATRON : 0 LCHKIN : - # RENEWALS : 0 # OVERDUE : 0 IUSE3 : 0 TOT CHKOUT : 0 TOT RENEW : 0 78508 78508 0 0 0 0 MAIN MAIN mnait 2026-08-18 6.60 0 AIT Thesis no.ET-11-24 30050120602486 2026-08-18 15:57:49 1 2026-08-18 20 0 0 0 0 MAIN MAIN mnait 2026-08-18 6.60 0 AIT Thesis no.ET-11-24 30050120602494 2026-08-18 15:57:49 2 2026-08-18 20 0 0 0 0 MAIN MAIN mnarc 2026-08-18 0 AIT Thesis no.ET-11-24 30050120368088 2026-08-18 15:57:49 2026-08-18 40