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Mathematical Problems in Engineering
Volume 2018, Article ID 3810492, 13 pages
Research Article

Joint Scheduling Optimization of Virtual Power Plants and Equitable Profit Distribution Using Shapely Value Theory

1North China Electric Power University, Beijing 102206, China
2Yan’an University, Bao’an, Yan’an, Shanxi 716000, China
3Academy of Chinese Energy Strategy, China University of Petroleum-Beijing, 18 Fuxue Road, Changping, Beijing 102249, China
4Beijing Energy Development Research Base, North China Electric Power University, Changping, Beijing 102206, China

Correspondence should be addressed to Huan-huan Li; moc.qq@470398249

Received 23 March 2017; Revised 29 November 2017; Accepted 16 January 2018; Published 25 February 2018

Academic Editor: Thomas Hanne

Copyright © 2018 Zhong-fu Tan et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


The installation capacity of wind and solar photovoltaic power is continually increasing, which makes renewable energy grid connection and power generation an important link of China’s power structure optimization. A virtual power plant (VPP) is an important way to help distributed energy resource grid connection and promote renewable energy industry development. To study the economic scheduling problem of various distributed energy resources and the profit distribution problem of VPP alliance, this study builds a separate operation scheduling model for individual VPP and a joint operation scheduling model for VPP alliance, as well as the profit distribution model. The case study verifies the feasibility and effectiveness of the proposed model. The sensitivity analysis provides information about VPP decision-making in accordance with the policy environment development trend.