基于气象因子的南京市冬季和夏季用电量预测研究

doi:10.3969/j.issn.1673-503X.2022.04.015

Abstract

Abstract:

Based on the hourly meteorological data, daily electricity consumption (EC), and hourly power load data from 2014 to 2016, the relationships between the variation of EC and meteorological factors in Nanjing were analyzed.The EC in Nanjing is featured with significant annual variation with two peaks in July-August and December-January and two valleys in April and October.Power load features a prominent 'weekend effect' in all four seasons.The diurnal variation of power load shows two peaks and two valleys.The two peak times are at 10:00 and 20:00.The two valley times vary with seasons.One is at 04:00 in both summer and winter, and the other is at 14:00 in winter and 18:00 in summer.The EC in Nanjing is closely related to the variation of weather conditions.The meteorological factors play various or even opposite roles on EC in different months.For example, in summer (autumn and winter), the greater the EC, the larger (smaller) is the daily temperature range in summer (autumn and winter).The heavier the EC, the higher (lower) is temperature in July-August (October-March).The influence of meteorological factors on the EC in summer is larger than in winter.The EC of Nanjing is mainly affected by temperature in winter, while is complicatedly affected by humidity and sunshine besides temperature in summer.The monthly forecast equation for the daily EC in winter and summer is set up by a stepwise regression method with different selected meteorological factors which show obvious inter-month variation.Forecasts of the EC in different months are conducted by considering different selected meteorological factors, providing an important reference for power dispatch.

Key words: Electricity consumption, Power load, Meteorological factors, Forecast

CLC Number:

Sheng-jie CHEN,Xin-ru TIAN,Ruan YAO,Lin JIANG. Forecast of electricity consumption in Nanjing based on meteorological factors in winter and summer[J]. Journal of Meteorology and Environment, 2022, 38(4): 127-135.

Figures/Tables 10

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月份	平均海平面气压X₁	平均气温X₂	最高气温X₃	最低气温X₄	气温日较差X₅	平均水汽压X₆	平均相对湿度X₇	日降水量X₈	平均风速X₉	日照时数X₁₀	平均露点温度X₁₁	日平均总云量X₁₂	日平均低云量X₁₃
12	0.41^**	-0.49^**	-0.49^**	-0.36^**	-0.06	-0.25^*	0.04	0.10	-0.11	0.04	-0.24^*	0.06	0.06
1	0.52^**	-0.69^**	-0.76^**	-0.39^**	-0.40^**	-0.38^**	0.15	0.13	-0.03	-0.32^**	-0.31^*	0.28^*	0.23^*
2	0.73^**	-0.62^**	-0.56^**	-0.54^**	-0.06	-0.46^**	-0.06	-0.09	-0.33^*	0.08	-0.45^**	-0.13	-0.21^*
6	0.06	0.23^*	0.21^*	0.29^*	0.03	0.26^*	0.04	0.04	-0.09	-0.07	0.23^*	0.10	0.06
7	-0.19	0.91^**	0.81^**	0.91^**	0.40^**	0.63^**	-0.77^**	-0.24^*	0.01	0.62^**	0.62^**	-0.69^**	-0.58^**
8	-0.60^**	0.92^**	0.88^**	0.87^**	0.47^**	0.49^**	-0.60^**	-0.16	0.26^*	0.63^**	0.44^**	-0.50^**	-0.25^*

月份	平均海平面气压X₁	平均气温X₂	最高气温X₃	最低气温X₄	气温日较差X₅	平均水汽压X₆	平均相对湿度X₇	日降水量X₈	平均风速X₉	日照时数X₁₀	平均露点温度X₁₁	日平均总云量X₁₂	日平均低云量X₁₃
12	0.45^**	-0.55^**	-0.57^**	-0.38^**	-0.10	-0.29^*	0.02	0.10	-0.01	0.01	-0.29^*	0.10	0.09
1	0.54^**	-0.71^**	-0.77^**	-0.42^**	-0.39^**	-0.40^**	0.13	0.12	-0.02	-0.31^*	-0.34^**	0.27^*	0.22^*
2	0.73^**	-0.67^**	-0.61^**	-0.56^**	-0.10	-0.47^**	-0.03	-0.05	-0.29^*	0.04	-0.46^**	-0.10	-0.17
6	-0.36^**	0.75^**	0.65^**	0.71^**	0.26^*	0.61^**	-0.09	-0.03	-0.21^*	0.26^*	0.57^**	-0.20	-0.17
7	-0.20	0.92^**	0.88^**	0.91^**	0.41^**	0.66^**	-0.76^**	-0.25^*	0.02	0.63^**	0.65^**	-0.69^**	-0.60^**
8	-0.60^**	0.92^**	0.89^**	0.87^**	0.49^**	0.50^**	-0.59^**	-0.15	0.25^*	0.62^**	0.45^**	-0.49^**	-0.25^*

月份	逐步回归方程	复相关系数	剩余标准差/万kWh	平均绝对误差/万kWh	平均相对误差/(%)
12	Y=-259.908X₂+198.54X₆+14590.4	0.58	9.43	503.92	3.52
1	Y=-157.147X₂-135.588X₃-1124.599X₆+380.003X₁₁+162.739X₁₃+22400.61	0.85	14.53	673.97	5.11
2	Y=169.641X₁-103.11X₃-490.71X₉-190.259X₁₀-168.744X₁₃-158107	0.81	18.39	833.23	7.31
6	Y=171.67X₁+193.42X₄+1082.18X₆-1396.183X₁₁-161839	0.43	26.18	795.87	53.80
7	Y=1191.71X₂+418.67X₄+1300.168X₆+149.24X₇-74.73X₁₀-3181.29X₁₁+77.47X₁₃-3374.88	0.96	9.81	474.49	3.18
8	Y=308.90X₂+517.62X₄-95.47X₇+205.39X₁₃+398.21	0.95	14.29	688.07	4.67

月份	逐步回归方程	复相关系数	剩余标准差/MW	平均绝对误差/MW	平均相对误差/(%)
12	Y=-191.564X₂+53.378X₄+93.093X₆+44.654X₁₀+35.822X₁₂+6874.962	0.69	4.38	221.77	3.23
1	Y=-86.001X₂-68.225X₃-515.516X₆+166.669X₁₁+84.452X₁₃+10686.06	0.85	7.19	334.20	5.30
2	Y=79.806X₁-77.371X₂-209.56X₉-112.956X₁₀-68.201X₁₃-74239.15	0.84	8.70	395.07	7.19
6	Y=120.25X₂+352.34X₆-62.87X₉-425.80X₁₁+3575.24	0.85	4.55	216.77	3.59
7	Y=140.75X₂+317.18X₄+85.15X₅+630.98X₆-48.45X₁₀-1202.62X₁₁-30.42X₁₂+34.98X₁₃+5160.59	0.96	4.86	234.44	3.22
8	Y=-26.49X₁+143.22X₃+258.29X₄-38.09X₇+95.30X₉+45.66X₁₂+52.69X₁₃+25382.06	0.95	7.29	361.92	5.00

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Forecast of electricity consumption in Nanjing based on meteorological factors in winter and summer

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