<b>Multi resolution electricity consumption data of Chinese cities estimated using open data</b>

Timely and spatially refined electricity consumption data are essential for supporting urban energy transition, electricity demand response, and supply-demand balancing strategies. However, publicly accessible datasets with high temporal resolution and city-level granularity remain scare, particularly in developing countries such as China. In this study, we generate electricity consumption estimate for 296 Chinese cities in 2022 at both daily and monthly resolutions. In addition, this study presents a top-down framework for estimating city-level daily and monthly electricity consumption by integrating open-access multi-source data, including nighttime light imagery and high-resolution meteorological variables. The validation results demonstrate a strong alignment between the estimated values and officially reported annual statistics, and the data exhibit consistent spatial-temporal patterns across different scenarios and seasons. This dataset addresses critical data gaps in urban-scale electricity research, offering a publicly available, cost-efficient, and highly scalable solution for multi-resolution electricity monitoring. It supports broad applications in energy policy design, urban sustainability assessment, and electricity system modeling, especially in data-constrained regions.