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Energies2018,11, 1282
Table8.Actual loadandforecastingresultsonDay2(Unit:MV).
Time/h ActualData BA-ELM ELM BP LSSVM
D2 0:00 813.56 823.65 831.48 808.98 817.28
D2 1:00 809.75 813.14 807.71 821.76 805.37
D2 2:00 814.06 805.71 808.58 791.03 798.56
D2 3:00 794.74 802.96 803.47 791.70 799.16
D2 4:00 809.89 807.84 817.35 800.06 805.06
D2 5:00 816.16 815.76 811.90 810.62 808.21
D2 6:00 828.37 827.97 839.11 834.82 823.81
D2 7:00 844.26 855.64 846.80 881.84 849.91
D2 8:00 824.92 831.49 831.84 847.35 832.55
D2 9:00 852.17 853.25 850.02 850.91 846.54
D2 10:00 863.06 870.05 864.05 860.95 859.72
D2 11:00 880.26 896.07 883.27 877.19 875.25
D2 12:00 883.78 891.19 894.20 882.91 880.90
D2 13:00 828.22 840.99 838.46 840.79 833.57
D2 14:00 821.18 846.60 839.96 830.01 831.78
D2 15:00 851.78 875.29 854.88 854.81 855.43
D2 16:00 871.49 897.56 878.00 892.13 874.37
D2 17:00 899.60 908.66 905.04 902.64 890.10
D2 18:00 901.80 910.90 904.57 906.42 897.73
D2 19:00 898.35 920.69 906.55 933.13 896.98
D2 20:00 908.94 938.02 927.70 929.86 926.43
D2 21:00 931.82 929.26 954.66 925.09 926.55
D2 22:00 891.29 892.19 898.24 887.12 887.74
D2 23:00 839.30 843.91 851.50 837.50 845.48
Table9.Actual loadandforecastingresultsonDay3(Unit:MV).
Time/h ActualData BA-ELM ELM BP LSSVM
D3 0:00 812.83 826.59 828.03 810.38 816.37
D3 1:00 801.64 810.06 799.93 821.78 804.09
D3 2:00 801.97 803.68 799.95 792.22 797.19
D3 3:00 796.35 803.46 800.56 790.13 797.01
D3 4:00 808.94 812.67 810.88 798.79 803.98
D3 5:00 816.21 810.10 811.44 808.49 806.53
D3 6:00 828.45 826.87 843.63 827.00 822.53
D3 7:00 847.85 846.77 844.31 877.13 846.64
D3 8:00 831.33 837.25 819.12 831.35 829.91
D3 9:00 853.77 851.47 843.37 843.03 845.06
D3 10:00 851.61 865.18 860.53 852.02 857.88
D3 11:00 878.35 895.21 876.79 881.66 872.19
D3 12:00 884.54 880.56 891.03 877.67 877.97
D3 13:00 832.52 837.68 837.29 839.94 830.52
D3 14:00 826.76 842.95 829.22 822.08 828.02
D3 15:00 857.72 873.55 857.38 853.94 851.38
D3 16:00 870.69 889.24 874.85 878.75 870.82
D3 17:00 897.52 907.94 898.13 900.71 886.03
D3 18:00 891.26 902.31 901.23 897.71 893.15
D3 19:00 891.92 909.41 892.96 917.94 891.46
D3 20:00 911.87 934.60 923.71 927.50 921.99
D3 21:00 929.45 928.95 949.86 925.33 923.44
D3 22:00 890.98 893.84 891.63 879.08 885.75
D3 23:00 842.39 842.59 848.01 836.70 843.36
WecommonlyconsidertheREintherangeof[−3%,3%]and[−1%,1%]asastandardtotestifythe
performanceoftheproposedmodel. Basedonthesetablesandfigures,wecandeterminethat: (1)on28
June, therelativeerrorsof theproposedmodelandotherswereall in therangeof [−3%,3%];onlyone
349
Short-Term Load Forecasting by Artificial Intelligent Technologies
- Title
- Short-Term Load Forecasting by Artificial Intelligent Technologies
- Authors
- Wei-Chiang Hong
- Ming-Wei Li
- Guo-Feng Fan
- Editor
- MDPI
- Location
- Basel
- Date
- 2019
- Language
- English
- License
- CC BY 4.0
- ISBN
- 978-3-03897-583-0
- Size
- 17.0 x 24.4 cm
- Pages
- 448
- Keywords
- Scheduling Problems in Logistics, Transport, Timetabling, Sports, Healthcare, Engineering, Energy Management
- Category
- Informatik