Energy Management in Smart Power Systems

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Review demonstrates AI-driven forecasting improves energy management in smart grids, highlighting dynamic tariffs' impact on usage behavior.

AI-driven forecasting enhances electricity management, facilitating improved efficiency and reduced costs.
The forecast technology predicts next-day demand peaks and weather impacts on renewable energy generation.
Review highlights how dynamic tariff schemes can incentivize consumers to adjust energy usage during low-cost periods.
Challenges like high costs and rural coverage must be addressed to optimize smart grid operations for a sustainable future.

Min-Kun Huang (2025) studied this question.

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Review demonstrates AI-driven forecasting improves energy management in smart grids, highlighting dynamic tariffs' impact on usage behavior.