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This invention provides a residential aggregator-based optimal energy management method, comprising the following steps: constructing an aggregator model, building generalized energy storage models for three types of residential appliances—batteries, HVAC systems, and electric vehicles—and aggregating them into a residential aggregator for centralized management; generating scheduling instructions for the aggregator, in the first decision-making stage, formalizing the optimization control process into a Markov decision process, interacting with the environment based on the Soft Actor-Critic framework, learning the optimal scheduling strategy, and tracking the upper-level power grid scheduling while ensuring operational constraints; decomposing the aggregator's control instructions, in the second decision-making stage, the residential aggregator generates scheduling plans for each appliance through a three-step decomposition algorithm to follow the aggregated power scheduling defined in the first decision-making stage. This invention achieves automated and integrated control of residential energy, improves the integration and intelligence level of the energy system, reduces operating costs, and enhances user comfort.