气候变化领域集成服务门户(CCPortal): Data-Driven Dynamical Control for Bottom-up Energy Internet System

CCPortal

DOI	10.1109/TSTE.2021.3110294
	Data-Driven Dynamical Control for Bottom-up Energy Internet System
	Hua, Haochen; Qin, Zhaoming; Dong, Nanqing; Qin, Yuchao; Ye, Maojiao; Wang, Zidong; Chen, Xingying; Cao, Junwei
发表日期	2022
ISSN	1949-3029
EISSN	1949-3037
起始页码	315
结束页码	327
卷号	13 期号:1
英文摘要	With the increasing concern on climate change and global warming, the reduction of carbon emission becomes an important topic in many aspects of human society. The development of energy Internet (EI) makes it possible to achieve better utilization of distributed renewable energy sources with the power sharing functionality introduced by energy routers (ERs). In this paper, a bottom-up EI architecture is designed, and a novel data-driven dynamical control strategy is proposed. Intelligent controllers augmented by deep reinforcement learning (DRL) techniques are adopted for the operation of each microgrid independently in the bottom layer. Moreover, the concept of curriculum learning (CL) is integrated into DRL to improve the sample efficiency and accelerate the training process. Based on the power exchange plan determined in the bottom layer, considering the stochastic nature of electricity price in the future power market, the optimal power dispatching scheme in the upper layer is decided via model predictive control. The simulation has shown that, under the bottom-up architecture, compared with the conventional methods such as proportional integral and optimal power flow, the proposed method reduces overall generation cost by 7.1% and 37%, respectively. Meanwhile, the introduced CL-based training strategy can significantly speed up the convergence during the training of DRL. Last but not least, our method increases the profit of energy trading between ERs and the main grid.
英文关键词	Erbium; Energy management; Internet; Control systems; Training; Stochastic processes; Power markets; Bottom-up; deep reinforcement learning; energy Internet; microgrid; stochastic system
语种	英语
WOS研究方向	Green & Sustainable Science & Technology ; Energy & Fuels ; Engineering, Electrical & Electronic
WOS类目	Science Citation Index Expanded (SCI-EXPANDED)
WOS记录号	WOS:000731149800031
来源期刊	IEEE TRANSACTIONS ON SUSTAINABLE ENERGY
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/280989
作者单位	Hohai University; Tsinghua University; University of Oxford; University of Cambridge; Nanjing University of Science & Technology; Brunel University; Tsinghua University
推荐引用方式 GB/T 7714	Hua, Haochen,Qin, Zhaoming,Dong, Nanqing,et al. Data-Driven Dynamical Control for Bottom-up Energy Internet System[J],2022,13(1).
APA	Hua, Haochen.,Qin, Zhaoming.,Dong, Nanqing.,Qin, Yuchao.,Ye, Maojiao.,...&Cao, Junwei.(2022).Data-Driven Dynamical Control for Bottom-up Energy Internet System.IEEE TRANSACTIONS ON SUSTAINABLE ENERGY,13(1).
MLA	Hua, Haochen,et al."Data-Driven Dynamical Control for Bottom-up Energy Internet System".IEEE TRANSACTIONS ON SUSTAINABLE ENERGY 13.1(2022).