The relationship between electricity consumption (EC) and temperature (T) influences the energy supply-demand balance within cities, and a nonlinear EC-T relationship has been widely documented at the city scale for this case, while the within-city spatial heterogeneity of the EC-T relation has been overlooked. Using Shenzhen, China, as a case study, this study aims to investigate the spatial variations in the relationship between electricity consumption and temperature at the intraurban scale. We first examined the EC-T relation by sector at the city scale using segmented regression models, and then further extrapolated this relation to the grid scale of 12 m using a population and floor area weighting method. Specifically, we assumed that EC by sector was associated with different functional zones and is equally proportional to population and floor area, so the local EC can be estimated by multiplying the sectorial EC by the mean ratio of local population and floor area. We found that the rate of change in EC with T per land area varied from 0 to 4.7 kWh/m2/°C, with a mean value of 0.01 kWh/m2/°C and a coefficient of variation (CV) of 3.0. Among function zones, the largest value of the rate of EC was observed in commercial areas, with a mean value of 0.05 kWh/m2/°C. The proportion of the temperature-sensitive electricity consumption to the total electricity consumption (TECP) varied from 9.7% to 49.3% in space, with the highest mean value of 40.5% occurring in residential areas. These findings provide effective strategies for reducing energy use through cooling measures, showing great practical implications for urban planning and energy management policies adapted to the local environment to ensure equitable and sustainable urban development.
Read full abstract