对美国国防气象卫星计划（defense meteorological satellite program，DMSP）上的操作线性扫描系统（operational linescan system，OLS）所获取的夜间灯光数据进行校正，结合省级电力消费量构建2000—2013年省级尺度电力消费模拟模型。模型的拟合优度为0.714 9，这表明模拟模型有效。在此基础上反演出市级、县级和栅格级电力消费量，最后采用全局空间自相关和局部空间自相关分析多尺度电力消费时空演变格局。结果表明： 2000—2013年中国电力消费呈现显著增长趋势。电力消费总量由2000年的13 606.29亿kWh增加为2013年的53 423.39亿kWh。京津冀地区、长三角地区和珠三角地区是高电力消费聚集区域，西部地区则呈现低电力消费集聚态势，可见电力消费量分布呈现胡焕庸线特征。栅格、省级、市级和县级尺度电力消费量呈现出一致的分布趋势，不同地区电力消费存在着差异性。市级尺度是模拟电力消费的有效行政单元。2013年12.9%的省份、16.56%的城市和40.95%的县域电力消费呈现出局域空间相关性。
In combination of the corrected operational linescan system on defense meteorological satellite program (DMSP-OLS) nighttime light data with provincial electric power consumptions, a provincial scale electric power consumption simulation model was structured for the years from 2000 to 2013. The fitting goodness of the model was tested to be 0.714 9, and this proved the effectiveness of the proposed model. On this basis, the electric power consumptions of prefectural, county and pixel scales were calculated, and the spatiotemporal pattern of multiscale electric power consumption was analyzed by global spatial autocorrelation and local spatial autocorrelation. Computation results indicated that the electric power consumption in China showed a significant growth trend from 2000 to 2013. Total electric power consumption increased from 1 360.629 billion kWh in 2000 to 5 342.339 billion kWh in 2013. It is also found that the Beijing-Tianjin-Hebei region, the Yangtze River Delta and the Pearl River Delta were the high electric power consumption zones, while the western region presented low electric power consumption. This power consumption distribution showed the characteristics of Hu line. The power consumptions of all different scales presented a consistent spatial distribution trend, and there were differences of electric power consumption in different regions. Prefectural scale was an effective administrative unit to simulate electric power consumption. 12.9% of provinces, 16.56% of prefectural, and 40.95% of counties in 2013 showed local spatial correlation in electric power consumption.
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