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Abstract
Abstract: This research aims to apply artificial intelligence (AI) algorithms to optimize the electricity distribution network, focusing on improving efficiency, responsiveness, and integration of renewable energy. Deep learning and reinforcement learning algorithms are used to learn energy load patterns and adjust distribution in real-time. Through simulation of the electricity distribution network, this research found a 15% increase in energy efficiency, a reduction in response time by 85%, a 10% increase in maximum load capacity, and a 25% increase in the use of renewable energy. Additionally, operational costs of the network decreased by 12% due to automation generated by AI. The innovation of this research lies in the efficient integration of renewable energy sources and load management through more accurate prediction. The research results show that applying AI in the electricity distribution network can provide an effective and sustainable solution to reduce power loss and operational costs, as well as support the use of renewable energy. Therefore, this research contributes to the development of a smarter and more environmentally friendly electricity distribution system.
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