Optimal Scheduling of Microgrid Based on Deep Deterministic Policy Gradient and Transfer Learning

Luqin Fan, Jing Zhang, Yu He, Ying Liu, Tao Hu and Heng Zhang
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Luqin Fan: College of Electrical Engineering, Guizhou University, Guiyang 550025, China
Jing Zhang: College of Electrical Engineering, Guizhou University, Guiyang 550025, China
Yu He: College of Electrical Engineering, Guizhou University, Guiyang 550025, China
Ying Liu: Power Grid Planning Research Center of Guizhou Power Grid Corporation, Guiyang 550002, China
Tao Hu: Guizhou Power Grid Corporation, Guiyang 550002, China
Heng Zhang: College of Electrical Engineering, Guizhou University, Guiyang 550025, China

Energies, 2021, vol. 14, issue 3, 1-15

Abstract: Microgrid has flexible composition, a complex operation mechanism, and a large amount of data while operating. However, optimization methods of microgrid scheduling do not effectively accumulate and utilize the scheduling knowledge at present. This paper puts forward a microgrid optimal scheduling method based on Deep Deterministic Policy Gradient (DDPG) and Transfer Learning (TL). This method uses Reinforcement Learning (RL) to learn the scheduling strategy and accumulates the corresponding scheduling knowledge. Meanwhile, the DDPG model is introduced to extend the microgrid scheduling strategy action from the discrete action space to the continuous action space. On this basis, this paper holds that a microgrid optimal scheduling TL algorithm on the strength of the actual supply and demand similarity is proposed with a purpose of making use of the existing scheduling knowledge effectively. The simulation results indicate that this paper can provide optimal scheduling strategy for microgrid with complex operation mechanism flexibly and efficiently through the effective accumulation of scheduling knowledge and the utilization of scheduling knowledge through TL.

Keywords: microgrid; optimal scheduling; reinforcement learning; transfer learning (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

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