摘要
为方便电能供应者提前规划和优化供电配置,采用空间自相关Moran指数和经济计量方法对江西省用电量的空间相关性及其驱动因素进行了实证分析。研究结果表明,各市用电量存在明显空间差异,高值和低值相互环绕。通过对最大信息系数筛选出的驱动因素进行定量分析,发现除出生率外,发电量、GDP、人口总数、劳动力和工业用电量对用电量的增加具有正向促进作用,工业用电量和GDP是决定电力消费的关键因素。
To facilitate pre-planning and optimal allocation for electricity suppliers,an empirical analysis of the spatial correlation of electricity consumption and its driving factors in Jiangxi Province was carried out using spatial autocorrelation Moran index and econometric methods.The results of the study show that there are obvious spatial differences in power consumption among cities,and the high and low values of power consumption surround each other.By quantitatively analyzing the driving factors screened by the maximum information coefficient,we found that,except for the birth rate,power generation,GDP,total population,labor force and industrial power consumption have positively contributed to the increase of power consumption,and industrial electricity consumption and GDP are the key factors determining electricity consumption.
作者
车金星
袁芳
黄婧文
万冰蓉
CHE Jinxing;YUAN Fang;HUANG Jingwen;WAN Binrong(School of Science;Key Laboratory of Engineering Mathematics and Advanced Computing;School of Information Engineering,Nanchang Institute of Technology,Nanchang 330099,China;Nanchang No.10 Middle School,Nanchang 330006,China)
出处
《南昌工程学院学报》
CAS
2024年第3期58-64,共7页
Journal of Nanchang Institute of Technology
基金
国家自然科学基金资助项目(71971105)
江西省高校人文社会科学研究项目(JY22202,TJ23101)
江西省教育厅科学技术研究项目(GJJ211926)。
关键词
电力消耗
空间相关性
负荷影响因素
最大信息系数
power consumption
spatial correlation
load influencing factors
maximum information factor