This research proposes the design and implementation of an AI-driven power distribution system integrated with intelligent load shedding techniques. The system dynamically monitors load demand and employs priority-based disconnection strategies to prevent system overloads and potential blackouts. This paper will deeply discuss the structure.
[pdf] Traditional electrical distribution networks are static and inefficient. To make the network active, an optimal dynamic network topology reconfiguration (DNTR) is proposed to control line switching and reconnect some loads to different substations such that the cost of electricity can be minimized. Problem formulations and. School of Electric Power Engineering, South China University of Technology, Guangzhou, China 3., Guangzhou, China With the increasing integration of renewable energy into the power grid, the traditional roles of the transmission and distribution. To address this, the research combines Selective Particle Swarm Optimization (SPSO) with the Extra Trees Classifier, a machine learning algorithm based on deep learning, to optimize dynamic distribution network reconfiguration.
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