Fast Distributed Demand Response Algorithm in Smart Grid

Qifen Dong; Li Yu; Wenzhan Song; Junjie Yang; Yuan Wu; Jun Qi

doi:10.1109/JAS.2017.7510529

Volume 4 Issue 2

Apr. 2017

IEEE/CAA Journal of Automatica Sinica

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Article Navigation > IEEE/CAA Journal of Automatica Sinica > 2017 > 4(2): 280-296

Qifen Dong, Li Yu, Wenzhan Song, Junjie Yang, Yuan Wu and Jun Qi, "Fast Distributed Demand Response Algorithm in Smart Grid," IEEE/CAA J. Autom. Sinica, vol. 4, no. 2, pp. 280-296, Apr. 2017. doi: 10.1109/JAS.2017.7510529

Citation:

Qifen Dong, Li Yu, Wenzhan Song, Junjie Yang, Yuan Wu and Jun Qi, "Fast Distributed Demand Response Algorithm in Smart Grid," IEEE/CAA J. Autom. Sinica, vol. 4, no. 2, pp. 280-296, Apr. 2017. doi: 10.1109/JAS.2017.7510529

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Fast Distributed Demand Response Algorithm in Smart Grid

doi: 10.1109/JAS.2017.7510529

Qifen Dong^{1
,
,},
Li Yu^2
,,
Wenzhan Song^3
,,
Junjie Yang^4
,,
Yuan Wu^2
,,
Jun Qi^2
,

1.
Department of Computer Science, Zhejiang Police College, Hangzhou 310053, China
2.
College of Information Engineering, Zhejiang University of Technology, Hangzhou 310014, China
3.
College of Engineering, University of Georgia, Athens, GA 30602, USA
4.
Department of Electrical and Information Engineering, Shanghai University of Electric Power, Shanghai 200090, China

Funds:

the National Natural Science Foundation of China 61202369

the NSFC-Zhejiang Joint Fund for the Integration of Industrialization and Informatization U1509219

More Information

Author Bio:
Li Yu received the B. S. degree in control theory from Nankai University, Tianjin, China, in 1982, and the M. S. and Ph. D. degrees from Zhejiang University, Hangzhou, China. He is currently a professor at the College of Information Engineering, Zhejiang University of Technology. He has authored or co-authored three books and over 200 journal or conference papers. His current research interests include wireless sensor networks, networked control systems, and motion control.(e-mail: lyu@zjut.edu.cn)

Wenzhan Song is now a professor in the College of Engineering, University of Georgia. His research mainly focuses on sensor web, smart grid and smart environment where sensing, computing, communication and control play a critical role and need a transformative study. His research has received 6 million+ research funding from NSF, NASA, USGS, Boeing, and etc. since 2005.(e-mail: wsong@uga.edu)

Junjie Yang received the B. E. and M. S. degrees both from Changchun University of Science and Technology, in 1998 and 2001, respectively, and the Ph. D. degree from Shanghai Jiao Tong University in 2005. He is a full professor at the College of Electronic and Information Engineering, Shanghai University of Electric Power. His research interests include wireless sensor networks, optical networks, and smart grid.(e-mail: yangjj@shiep.edu.cn)

Yuan Wu received the Ph. D. degree in electronic and computer engineering from Hong Kong University of Science and Technology, in 2010. He was the visiting scholar in Princeton University and Georgia State University in 2009 and 2013, respectively. During 2010-2011, he was the postdoctoral research associate at HKUST. He is currently an associate professor in the College of Information Engineering, Zhejiang University of Technology. His research interests include resource allocations for cognitive radio networks, game theories and their applications in communication networks.(e-mail: iewuy@zjut.edu.cn)

Jun Qi is currently a lecturer at the College of Information Engineering, Zhejiang University of Technology. She received the Ph. D. degree (2009) in power system and its automation from Zhejiang University. Her research interests include power system analysis and control, renewable energy generation technology.(e-mail: qijun@zjut.edu.cn)
Corresponding author: Qifen Dong is currently a lecturer in the Department of Computer Science, Zhejiang Police College, Hangzhou, China. She received the B. E. degree in electronic information engineering and the Ph. D. degree in control theory and control engineering from Zhejiang University of Technology, Hangzhou, China, in 2007 and 2013, respectively. Her research interests include wireless sensor networks, smart grids, and embedded system. Corresponding author of this paper.(e-mail: dongqifen@zjjcxy.cn)
Received Date: 2016-06-03
Accepted Date: 2016-09-30

Abstract

Abstract

This paper proposes a fast distributed demand response (DR) algorithm for future smart grid based on primaldual interior method and Gaussian belief propagation (GaBP) solver. At the beginning of each time slot, each end-user/energysupplier exchanges limited rounds of messages that are not private with its neighbors, and computes the amount of energy consumption/generation locally. The proposed demand response algorithm converges rapidly to a consumption/generation decision that yields the optimal social welfare when the demands of endusers are low. When the demands are high, each end-user/energysupplier estimates its energy consumption/generation quickly such that a sub-optimal social welfare is achieved and the power system is ensured to operate within its capacity constraints. The impact of distributed computation errors on the proposed algorithm is analyzed theoretically. The simulation results show a good performance of the proposed algorithm.
- Demand response (DR),
- distributed primal-dual interior algorithm,
- social welfare

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References(38)

References

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Fast Distributed Demand Response Algorithm in Smart Grid

doi: 10.1109/JAS.2017.7510529

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