Dueling-DQN在空调节能控制中的应用

Application of Dueling-DQN in Air Conditioning Control for Energy Saving

针对电信机房空调运行耗电量大,空调自动控制系统设计困难的问题,提出了一种规则约束和DuelingDQN算法相结合的空调节能控制方法.该方法能根据不同机房环境自适应学习建模,在保证机房室内温度在规定范围的前提下,节省空调耗电量.同时针对实际机房应用场景,设计节能控制算法中的状态,动作和奖励函数,并采用深度强化学习算法Dueling-DQN提高模型表达能力和学习效率.在电信机房实际验证结果表明:该控制方法与空调默认设定参数运行相比节能18.3%,并可以很方便推广到不同环境场景的机房环境中,为电信机房节能减排提供解决方案.

To tackle the problems of large power consumption and intricate design of the automatic control system for air conditioning in a telecommunication room, this study proposes an energy-saving control method based on the DuelingDQN algorithm and rule constraint for mechanical control system design. With the ability to learn modeling adaptively according to the environments of different computer rooms, this method can save the power consumption of air conditioning while ensuring the indoor temperature in the specified range. Moreover, according to the actual application scenarios of computer rooms, the states, actions and reward functions of the energy-saving control algorithm are designed.Besides, a deep reinforcement learning algorithm Dueling-DQN is used to improve the model expression ability and learning efficiency. The results of actual verification in telecommunication rooms show that the control method can save energy by 18.3% compared with the air conditioning at default parameters. It can be easily extended to machines in different environmental scenarios to provide solutions for energy conservation and emission reduction of telecommunication rooms.