AI-Driven Federated Learning Frameworks for Privacy-Preserving Smart Urban Energy Management

The growing complexity of urban energy systems with smartness requires intelligent solutions that are privacy friendly to manage the distributed energy resources efficiently. This chapter introduces a federated learning model that is AI-powered and in this system, model training is performed in an intelligent grid, micro grid, and IoT-based devices, without the exchange of raw data. The strategy improves accuracy in load forecasting, efficiency of energy use, and lessens the amount of overhead in communication besides maintaining data privacy and security. The framework combines edge computing and state-of-the-art AI to promote scalable and adaptive energy management to add to sustainable, resilient, and human-centric smart city ecosystems.

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