Framework and strategy design of demand response scheduling for balancing wind power fluctuation

被引:7
作者
Yao, Jianguo [1 ]
Yang, Shengchun [1 ,2 ]
Wang, Ke [1 ]
Zeng, Dan [1 ]
Mao, Wenbo [1 ]
Geng, Jian [1 ]
机构
[1] China Electric Power Research Institute (Nanjing), Nanjing
[2] School of Electrical and Electronic Engineering, Huazhong University of Science and Technology, Wuhan
来源
Dianli Xitong Zidonghua/Automation of Electric Power Systems | 2014年 / 09期
关键词
Demand response (DR); Interaction; Multi-agent; Rolling coordination; Scheduling; Wind power fluctuation;
D O I
10.7500/AEPS20130602003
中图分类号
学科分类号
摘要
Fast increase of intermittent energy such as wind energy is presenting great challenges to the traditional operation and control of power grids. To solve this problem, firstly, the fluctuation characteristic of wind power and the load characteristic of demand response (DR) are analyzed. Based on that, the overall technical framework of DR scheduling is proposed. Then, a multi-agent scheme is given. Furthermore, the multi-time scale rolling coordinated scheduling strategy which combines day-ahead scheduling, hours-ahead scheduling and real-time dispatch is studied. The effectiveness of the scheme, model and strategy proposed are demonstrated by simulation results on the IEEE 39 bus system. The experiments also show that the appropriate DR scheduling is feasible to balance the fluctuation of wind power and provides more peak-shaving and reserve service for grid-connection of new energy. ©2014 State Grid Electric Power Research Institute Press.
引用
收藏
页码:85 / 92
页数:7
相关论文
共 21 条
[1]  
Yao J., Yang S., Wang K., Et al., Concept and research framework of smart grid 'source-grid-load' interactive operation and control, Automation of Electric Power Systems, 36, 21, pp. 1-6, (2012)
[2]  
Zhang Q., Wang X., Wang J., Et al., Survey of demand response research in deregulated electricity markets, Automation of Electric Power Systems, 32, 3, pp. 97-106, (2008)
[3]  
Wang B., Li Y., Gao C., Demand side management outlook under smart grid infrastructure, Automation of Electric Power Systems, 33, 20, pp. 17-22, (2009)
[4]  
Tan Z., Chen G., Zhao J., Et al., Optimization model for designing peak-valley time-of-use power price of generation side and sale side at the direction of energy conservation dispatch, Proceedings of the CSEE, 29, 1, pp. 55-62, (2009)
[5]  
Liu X., Wang B., Li Y., Et al., Day-ahead generation scheduling model considering demand side interaction under smart grid paradigm, Proceedings of the CSEE, 33, 1, pp. 30-39, (2013)
[6]  
Tuan L.A., Bhattacharya K., Competitive framework for procurement of interruptible load services, IEEE Trans on Power Systems, 18, 2, pp. 460-465, (2003)
[7]  
Huang K.Y., Chin H.C., Huang Y.C., A model reference adaptive control strategy for interruptible load management, IEEE Trans on Power Systems, 19, 1, pp. 683-689, (2003)
[8]  
Huang K., Huang Y., Integrating direct load control with interruptible load management to provide instantaneous reserves for ancillary services, IEEE Trans on Power Systems, 19, 3, pp. 1626-1634, (2004)
[9]  
Callaway D.S., Hiskens I.A., Achieving control ability of loads, Proceedings of the IEEE, 99, 1, pp. 184-199, (2011)
[10]  
A national assessment of demand response potential, (2009)