"Integrated Hourly Electricity Load and Meteorological Dataset for Smart Grid Demand Analysis and Forecasting"

"This dataset delivers a high-resolution, city-scale representation of Delhi\u2019s electricity demand behavior through the rigorous integration of hourly electrical load measurements with temporally aligned meteorological observations for the National Capital Territory of Delhi. Capturing the intricate and non-linear coupling between atmospheric forcing and urban energy consumption, the dataset reflects Delhi\u2019s pronounced climatic heterogeneity, including extreme summer heatwaves, monsoon-driven humidity regimes, transitional shoulder seasons, and winter cold spells associated with atmospheric stagnation. These conditions critically shape electricity demand through air-conditioning and heating loads, behavioral adaptations, and evolving urban infrastructure. The dataset synchronizes hourly load profiles with key weather variables\u2014such as ambient temperature, relative humidity, wind speed, and associated atmospheric indicators\u2014thereby enabling detailed analysis of weather-sensitive demand fluctuations and peak-load stress phenomena. Structured for advanced energy analytics, it is well suited for state-of-the-art time-series modeling, including deep learning, transformer-based architectures, hybrid physics-informed approaches, and climate-aware forecasting frameworks. The dataset supports investigations into heatwave-induced demand surges, demand response potential, dynamic tariff design, renewable energy integration, and power system resilience under climate variability and extreme events. By providing a unified, machine-readable depiction of the electricity\u2013weather nexus in one of the world\u2019s largest and most climate-vulnerable megacities, this dataset facilitates reproducible research, robust model benchmarking, and evidence-based policy analysis for smart grid planning, sustainable urban energy management, and climate-adaptive infrastructure development in Delhi."