Characteristics of power load in Wuhan and its relationship with meteorological factors

Abstract

In this paper, the 15 min refined power load data、daily temperature and precipitation data of Wuhan from 2013 to 2018 are used to calculate out and analyse the characteristic indexes of power load, with the internal composition and changing law being explored. The results show that: (1) the power load and the daily load peak-valley difference in Wuhan have been broken for new records in recent years, the duration and intensity of high temperature have the most significant impact on air conditioning load in summer. The power load shows obvious "double peak and double valley" characteristics with the season. (2) The power load is much higher in summer than in other seasons, followed by winter. The distributions of diurnal variation characteristics are "high in the day and low in the night" in four seasons. (3) The power load of working days and weekends is significantly higher than that in holidays, and the power load is slightly higher on weekdays than on weekends the morning peak load is the largest on workdays, while the evening peak load is the largest on weekends and holidays. (4) Meteorological factors have an important impact on the electricity consumption of the whole society, and the relationship between meteorological sensitive load and daily average temperature is most significant in summer. When the average temperature is higher than the initial and sensitive value, the power load increases more obviously with the temperature rise. (5) No matter there is precipitation or not, the relationship between meteorological sensitive load and daily average temperature in summer is very close. Without precipitation, the power load has the best correlation with daily average temperature; the correlation between meteorological sensitive load and daily average temperature shows a downward trend in a rainy day, which reflects that the physical processes and mechanisms of precipitation can affect temperature and hence power load.

Keywords

• power load
• temperature
• air conditioning load
• the curve of daily load
• 1 ℃ effect