Title
ADMM Empowered Distributed Computational Intelligence for Internet of Energy
Abstract
Internet of Energy (IoE), the paradigm of applying Internet of Things (IoT) to energy management systems, aims to improve energy systems' efficiency and reliability by enhancing connectivity and interoperability among geographically distributed energy devices. This requires distributed computational intelligence responsible for data processing and decision making of the energy devices. To achieve distributed, scalable, and privacy-protected energy management in IoE, this article proposes using Alternating Direction Method of Multipliers (ADMM) as the theoretical framework to design the distributed computational intelligence in IoE. In the first place, a brief introduction of ADMM for solving energy management problems is given. Based on the ADMM framework, a distributed intelligence system is designed for each decision maker in energy systems. With the distributed intelligence, decision makers can interact with each other to achieve system-wide goals of energy management without disclosing their private data. Moreover, we provide some examples of ADMM applications in practical distributed energy management in IoE and discuss the challenges of ADMM implementation in IoE. Lastly, a joint computing and networking resources management architecture is proposed to meet the challenges. The result of a case study shows that this architecture can reduce communications and computing costs of ADMM implementation.
Year
DOI
Venue
2019
10.1109/MCI.2019.2937611
IEEE Computational Intelligence Magazine
Keywords
Field
DocType
Internet of Things,Big Data,Energy management,Computer architecture,Energy efficiency
Resource management,Energy management,Computational intelligence,Efficient energy use,Computer science,Interoperability,Distributed generation,Artificial intelligence,Big data,Distributed computing,Scalability
Journal
Volume
Issue
ISSN
14
4
1556-603X
Citations 
PageRank 
References 
0
0.34
0
Authors
6
Name
Order
Citations
PageRank
Weifeng Zhong19910.88
Kan Xie235128.49
Yi Liu346627.80
Chao Yang45112.05
Shengli Xie52530161.51
Yan Zhang65818354.13