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Mathematical Problems in Engineering
Volume 2016 (2016), Article ID 4070251, 10 pages
Research Article

A Joint Scheduling Optimization Model for Wind Power and Energy Storage Systems considering Carbon Emissions Trading and Demand Response

1School of Economics and Management, Beijing University of Aeronautics and Astronautics, Beijing 100191, China
2School of Economics and Management, North China Electric Power University, Beijing 102206, China

Received 16 November 2015; Revised 11 January 2016; Accepted 27 January 2016

Academic Editor: Jinyun Yuan

Copyright © 2016 Yin Aiwei 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.


To reduce the influence of wind power random on system operation, energy storage systems (ESSs) and demand response (DR) are introduced to the traditional scheduling model of wind power and thermal power with carbon emission trading (CET). Firstly, a joint optimization scheduling model for wind power, thermal power, and ESSs is constructed. Secondly, DR and CET are integrated into the joint scheduling model. Finally, 10 thermal power units, a wind farm with 2800 MW of installed capacity, and  MW ESSs are taken as the simulation system for verifying the proposed models. The results show backup service for integrating wind power into the grid is provided by ESSs based on their charge-discharge characteristics. However, system profit reduces due to ESSs’ high cost. Demand responses smooth the load curve, increase profit from power generation, and expand the wind power integration space. After introducing CET, the generation cost of thermal power units and the generation of wind power are both increased; however, the positive effect of DR on the system profit is also weakened. The simulation results reach the optimum when both DR and CET are introduced.