Optimal Dispatch of Integrated Energy System Based on Deep Reinforcement Learning
In allusion to the uncertainty of renewable energy and load in integrated energy system,an optimal dispatch meth-od based on deep reinforcement learning was proposed.Firstly,the methodology of the deep reinforcement learning was ex-pounded,and an optimal dispatch model based on the deep re-inforcement learning,in which the state space,action space and reward function were designed,was proposed.Secondly,the model solving process based on asynchronous advantage actor-critic(abbr.A3C)algorithm was designed.Finally,the results of example simulation show that the proposed method can ad-aptively respond to the uncertainty of source and loads,and its optimization effect is similar to that of traditional mathematical programming method.
integrated energy systemoptimal dispatchdeep reinforcement learninguncertainty sources and loads
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