A consensus and incentive program for charging piles based on consortium blockchain

Qingsu He, State Grid Electronic Commerce Co., LTD., Yu Xu, Yong Yan, Junsheng Wang, Qingzhi Han, Lili Li, State Grid Electronic Commerce Co., LTD., State Grid Zhejiang Electric Power Company, State Grid Electronic Commerce Co., LTD, State Grid Electronic Commerce Co., LTD, State Grid Electronic Commerce Co., LTD
2018 CSEE Journal of Power and Energy Systems  
Charging piles are used for charging electric vehicles and are directly accessible to users in an energy internet entrance, while playing an important role in energy consumption. Currently, each enterprise constructs the center of operation and maintenance of their systems independently, along with their respective APP payment programs. This results in high operating costs, poor user experience, and low utilization rate of the pile, which limits the promotion and popularization of electric
more » ... les. To overcome this limitation, there is a need for a multi-center, fair, and transparent consortium blockchain, which can conform to the application requirements of a unified payment system and accommodate a range of diverse enterprise charging piles. In this paper, the design for a consensus and incentive program for consortium blockchain is presented. First, the application status of blockchain in an energy internet is described. Then, the logical structure and hierarchical model of the consortium blockchain are analyzed. Next, multicycle accounting and limiting the amount of accounting nodes in each round is presented to ensure the overhead of consensus remain constant. Finally, the accounting incentive mechanism and the bidding encouragement strategy based on "electric beans" are designed. Index Terms-Charging pile, consortium blockchain, energy internet, payment solution, power profit bean. Junsheng Wang received the B.S. degree in Communications Engineering from Beijing University of Posts and Telecommunications, Beijing, in 2003. He is the senior engineer and his research interests include Communication and information technology, Machine Learning (ML), and Internet Technology. Qingzhi Han received the M.S. degree in control engineering from University of Science and Technology Liaoning, Anshan, in 2016. His research interests include human face recognition and machine learning (ML). Lili Li received the M.S. degree in Mechatronic engineering from North University of China, Taiyuan, in 2010. Her research interests include wireless communication and internet technology.
doi:10.17775/cseejpes.2017.00960 fatcat:xzsecavjaffjjb2qwxgcncuwkq