This study explores energy distribution optimization in smart grids, integration of renewable energy sources, and predictive maintenance implementation to enhance efficiency, reliability, and sustainability of urban energy systems. Data were collected through network sensors, energy monitoring systems, maintenance logs, and interviews with network operators. Analysis was conducted using optimization algorithms, computer simulations, and qualitative evaluation. The results indicate that the application of these strategies can reduce energy losses by 12%, increase renewable energy contribution up to 18%, decrease equipment downtime by 20%, and improve peak load efficiency by 15%. The study confirms that integrating distribution optimization, renewable energy, and predictive maintenance provides significant synergistic impacts on urban energy management while supporting the transition toward sustainable smart cities.
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