Resilient Smart Grid Management through Weather-Informed and Economic Dispatch

The transition to decentralised, renewable-driven power systems introduces new challenges for grid affordability and resilience. This paper presents Climate- Adaptive Grid Intelligence (ClimaGrid), an AI-assisted, multi-layer control framework designed to optimise distributed energy resource (DER) dispatch under dynamic environmental and market conditions. ClimaGrid integrates three coordinated mechanisms: Adaptive Priority-Aware Dispatch (APAD) for load profile smoothing, weather-informed resilience control for hazard response, and market-responsive energy allocation to minimise operational cost. Using a real-world dataset comprising load demand, PV and wind generation, and spot market prices, we demonstrate that ClimaGrid reduces peak load by 29.2% and peak-to-average ratio by 17.6%. In resilience simulations, it achieves full recovery within 12 minutes of a weather-induced generation drop, over three times faster than conventional rule-based strategies. Furthermore, ClimaGrid lowers grid import costs by 27.4% during price spikes, while maintaining DER coverage above 60%. These results validate ClimaGrid as a robust and economically efficient solution for future smart grid operation.<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sup>