Smart generation control based on multi-agent reinforcement learning with the idea of the time tunnel

	Smart generation control based on multi-agent reinforcement learning with the idea of the time tunnel
	Lei Xi; Jianfeng Chen; Yuehua Huang; Yanchun Xua; Lang Liu; Yimin Zhou; Yudan Li
刊名	Energy
	2018
文献子类	期刊论文
英文摘要	One of the significant solutions for hazy is to reduce carbon emission by introducing renewable energy on a large scale. However, the large-scale integration of new energy will result in stochastic disturbance to power grid. Therefore it becomes a top priority to make new energy compatible with power system. The PDWoLF-PHC(l) based on the idea of time tunnel is to be proposed in this paper. Optimal strategy could be obtained by adopting the variable learning rate in a variety of complex operating environments, and thence it can deal with stochastic disturbance caused by massive integrations of new energy and distributed energy sources to the power grid, which is difficult for traditional centralized AGC. The proposed algorithm is simulated to be effective according to the improved IEEE standard two-area loadfrequency control power system model and the Central China Power Grid model. Compared with the traditional smart ones, the proposed algorithm is characterized with faster convergence and stronger robustness, which makes it able to reduce carbon emission and enhance utilization rate of the new energy.
URL标识	查看原文
语种	英语
内容类型	期刊论文
源URL	[http://ir.siat.ac.cn:8080/handle/172644/13665]
专题	深圳先进技术研究院_集成所
推荐引用方式 GB/T 7714	Lei Xi,Jianfeng Chen,Yuehua Huang,et al. Smart generation control based on multi-agent reinforcement learning with the idea of the time tunnel[J]. Energy,2018.
APA	Lei Xi.,Jianfeng Chen.,Yuehua Huang.,Yanchun Xua.,Lang Liu.,...&Yudan Li.(2018).Smart generation control based on multi-agent reinforcement learning with the idea of the time tunnel.Energy.
MLA	Lei Xi,et al."Smart generation control based on multi-agent reinforcement learning with the idea of the time tunnel".Energy (2018).