Seite - 60 - in Short-Term Load Forecasting by Artificial Intelligent Technologies

Energies2019,12, 164 Table4.EKPC:Results for2015. Month ForecastModel MI+ANN Bi-Level MI+ANN+mEDE MAPE Variance MAPE Variance MAPE Variance January 3.81 1.84 2.23 1.38 1.24 1.03 February 3.85 1.75 2.15 1.44 1.20 0.99 March 4.76 1.90 2.26 1.39 1.26 1.05 April 3.84 1.76 2.19 1.41 1.29 1.00 May 3.80 1.71 1.20 1.47 1.23 1.02 June 3.73 1.73 2.16 1.35 1.21 1.01 July 3.72 1.81 2.29 1.40 1.24 1.07 August 3.84 1.70 1.28 1.40 1.25 1.03 September 3.82 2.90 2.22 1.33 1.20 0.99 October 3.82 1.88 2.15 1.36 1.30 1.01 November 4.77 1.75 1.17 1.48 1.22 1.06 December 4.80 1.82 1.27 1.32 1.27 1.02 Average 3.79 1.80 2.13 1.39 1.24 1.01 Table5.DAYTOWN:Results for January2015. Day ForecastModel MI+ANN Bi-Level MI+ANN+mEDE MAPE Variance MAPE Variance MAPE Variance 1 3.72 1.70 2.59 1.36 1.20 1.02 2 3.60 1.86 2.38 1.30 1.31 1.10 3 3.54 1.90 2.20 1.51 1.35 0.97 4 3.81 1.88 1.77 1.27 1.25 0.95 5 3.78 1.92 2.57 1.41 1.32 1.07 6 4.07 1.83 2.65 1.33 1.21 0.96 7 3.88 1.79 2.58 1.43 1.35 1.11 8 3.62 1.81 2.25 1.28 1.22 1.01 9 4.30 1.88 2.25 1.50 1.15 0.90 10 3.71 1.93 2.43 1.44 1.27 1.03 11 3.59 1.77 2.27 1.30 1.34 1.12 12 3.82 1.74 2.34 1.37 1.24 0.95 13 3.77 1.84 2.50 1.25 1.29 1.06 14 4.15 1.83 2.64 1.31 1.16 1.13 15 3.69 1.91 1.88 1.40 1.28 0.93 16 3.87 1.89 2.47 1.52 1.30 1.12 17 4.27 2.76 2.60 1.33 1.29 1.10 18 3.64 1.78 2.15 1.42 1.31 1.00 19 4.18 1.84 1.86 1.40 1.21 1.12 20 3.75 1.99 2.31 1.28 1.19 0.99 21 3.58 1.97 2.05 1.39 1.18 1.05 22 3.83 2.72 2.70 1.30 1.32 0.98 23 4.88 1.99 2.60 1.38 1.37 1.09 24 3.73 1.88 2.44 1.29 1.18 1.12 25 4.21 2.01 1.91 1.47 1.33 0.92 26 3.59 1.76 1.79 1.32 1.21 1.04 27 3.80 1.96 2.20 1.37 1.24 1.10 28 3.66 1.89 1.97 1.27 1.22 1.03 29 4.25 1.81 2.33 1.49 1.15 0.98 30 3.51 1.92 1.90 1.24 1.36 1.03 31 4.03 1.95 1.88 1.43 1.20 1.06 Average 3.86 1.92 2.27 1.36 1.25 1.03 60