计及自适应接入的家用空调协同调控策略OA

A collaborative control strategy for domestic air conditioners with adaptive access is proposed addressing communication barri-ers caused by diverse and incompatible device protocols in heterogeneous domestic air conditioners,along with low computational efficien-cy in real-time regulation.First,the domestic air conditioner information interaction architecture is constructed,and the adaptive access method is proposed on this basis.Then,the deep reinforcement learning multi-conditioner collaborative control strategy is developed,and the soft-max sampling strategy and the prioritized experience replay mechanism are introduced to improve the MAD3QN algorithm,and the SMPER-MAD3QN algorithm is proposed.Finally,a centralized training with decentralized execution is implemented based on SMPER-MAD3QN,which allows multiple air conditioners to collaboratively participate in the regulation of the algorithm.The simulation results measured that the packet loss rate of multi-protocol domestic air conditioner information interaction is 0.36%,and the interaction latency is lower than 25ms,which indicates that the adaptive access can significantly shorten the real-time decision-making time and realize the unified management and control of multi-protocol domestic air conditioner.Meanwhile,the proposed algorithm realizes the collaborative participation of multiple air conditioners in demand response(DR)under the premise of guaranteeing the comfort of users,and the algo-rithm has excellent robustness,which improves the flexibility and reliability of the dispatchable resources on the demand side.