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计及自适应接入的家用空调协同调控策略

石坤 胡祥 陈宋宋 祁兵 樊其锋 宫飞翔 刘颖

电力需求侧管理2025,Vol.27Issue(5):43-49,7.
电力需求侧管理2025,Vol.27Issue(5):43-49,7.DOI:10.3969/j.issn.1009-1831.2025.05.007

计及自适应接入的家用空调协同调控策略

Collaborative control strategy for household air conditioners with adaptive access

石坤 1胡祥 2陈宋宋 1祁兵 2樊其锋 3宫飞翔 1刘颖4

作者信息

  • 1. 需求侧多能互补优化与供需互动技术北京市重点实验室(中国电力科学研究院有限公司),北京 100192
  • 2. 华北电力大学 电气与电子工程学院,北京 102206
  • 3. 广东美的制冷设备有限公司,广东 佛山 528311
  • 4. 国网江苏省电力有限公司 营销服务中心,南京 210019
  • 折叠

摘要

Abstract

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.

关键词

家用空调/自适应接入/深度强化学习/集中式训练分布式执行/需求响应

Key words

household air conditioner/adaptive access/deep reinforcement learning/centralized training with decentralized execution/de-mand response

分类

信息技术与安全科学

引用本文复制引用

石坤,胡祥,陈宋宋,祁兵,樊其锋,宫飞翔,刘颖..计及自适应接入的家用空调协同调控策略[J].电力需求侧管理,2025,27(5):43-49,7.

基金项目

国家电网有限公司科技项目(5400-202355570A-3-2-ZN) (5400-202355570A-3-2-ZN)

电力需求侧管理

1009-1831

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