Optimal Control Strategy of Air Conditioning Energy Consumption Based on LSTM and DDPG
Building energy consumption is growing rapidly,and the contradiction between energy supply and demand is seri-ous.Aiming at the problem of high energy consumption and low energy efficiency of air conditioning system,this paper proposes an air conditioning control strategy based on LSTM and DDPG.This paper abstracts the energy consumption optimization problem of air conditioning into reinforcement learning problem,establishes the markov decision process model of air conditioning,and uses DDPG algorithm to optimize the control strategy of air conditioning.In order to further improve the model training efficiency,this pa-per proposes a training energy consumption prediction model based on LSTM algorithm to simulate the interaction environment with an agent,and solves the problem of long convergence time for online training without model reinforcement learning method.Finally,a factory air conditioning system is taken as the research object for the experiment,the experimental results show that the algorithm proposed in this paper has fast convergence speed,and can effectively reduce the operation energy consumption.
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