AI-Based Energy Management of Net-Zero Energy Buildings Through Renewable Integration and Storage
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Keywords:
Energy management, net-zero energy buildings, renewable integration, renewable energy storage, intelligent energy controlAbstract
This paper explores the role of AI in energy management of NZEBs, emphasizing renewable
integration and storage strategies, and presents future research directions to enhance efficiency, resilience,
and cost-effectiveness. Net-zero energy buildings (NZEBs) represent a transformative approach to
sustainable architecture, integrating advanced renewable energy technologies, energy-efficient designs, and
intelligent control strategies to achieve an annual energy balance between consumption and on-site
renewable generation. The increasing complexity of NZEB energy systems, driven by fluctuating
renewable generation, variable demand patterns, and multi-scale energy storage, has created the need for
advanced energy management strategies. Artificial intelligence (AI) techniques, particularly those
leveraging machine learning, reinforcement learning, and optimization algorithms, offer significant
potential for improving energy efficiency, operational flexibility, and occupant comfort.
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