Does Explicit Prediction Matter in Energy Management Based on Deep Reinforcement Learning?

• URL: http://arxiv.org/abs/2108.05099v1
• Date: Wed, 11 Aug 2021 08:52:42 GMT
• Title: Does Explicit Prediction Matter in Energy Management Based on Deep Reinforcement Learning?
• Authors: Zhaoming Qin, Huaying Zhang, Yuzhou Zhao, Hong Xie, and Junwei Cao
• Abstract summary: We present the standard DRL-based energy management scheme with and without prediction. The simulation results demonstrate that the energy management scheme without prediction is superior over the scheme with prediction. This work intends to rectify the misuse of DRL methods in the field of energy management.
• Score: 2.82357668338266
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: As a model-free optimization and decision-making method, deep reinforcement learning (DRL) has been widely applied to the filed of energy management in energy Internet. While, some DRL-based energy management schemes also incorporate the prediction module used by the traditional model-based methods, which seems to be unnecessary and even adverse. In this work, we present the standard DRL-based energy management scheme with and without prediction. Then, these two schemes are compared in the unified energy management framework. The simulation results demonstrate that the energy management scheme without prediction is superior over the scheme with prediction. This work intends to rectify the misuse of DRL methods in the field of energy management.

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