A Robust Reserve Scheduling Method Considering Asymmetrical Wind Power Distribution

Guanzhong Wang; Qiaoyan Bian; Huanhai Xin; Zhen Wang

doi:10.1109/JAS.2017.7510652

Volume 5 Issue 5

Aug. 2018

IEEE/CAA Journal of Automatica Sinica

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Guanzhong Wang, Qiaoyan Bian, Huanhai Xin and Zhen Wang, "A Robust Reserve Scheduling Method Considering Asymmetrical Wind Power Distribution," IEEE/CAA J. Autom. Sinica, vol. 5, no. 5, pp. 961-967, Sept. 2018. doi: 10.1109/JAS.2017.7510652

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Guanzhong Wang, Qiaoyan Bian, Huanhai Xin and Zhen Wang, "A Robust Reserve Scheduling Method Considering Asymmetrical Wind Power Distribution," IEEE/CAA J. Autom. Sinica, vol. 5, no. 5, pp. 961-967, Sept. 2018. doi: 10.1109/JAS.2017.7510652

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A Robust Reserve Scheduling Method Considering Asymmetrical Wind Power Distribution

doi: 10.1109/JAS.2017.7510652

Department of the Electrical Engineering, Zhejiang University, Hangzhou 310027, China

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the National High Technology Research and Development Program of China 2015AA050202

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Author Bio:
Guanzhong Wang received the B. Eng. degree in electrical engineering from Zhejiang University, China, in 2013. He is currently working toward the Ph. D. degree with the Department of Electrical Engineering, Zhejiang University, China. His research interests include power system operation and planning, renewable energy integration, and ancillary services. (e-mail: 11510002@zju.edu.cn)

Qiaoyan Bian (M'13) received the B. Eng. and the Ph. D. degrees in electrical engineering from Zhejiang University, China, in 2008 and 2015, respectively. From March 2010 to April 2013, she was a training jointly Doctoral Student with the Electrical and Computer Engineering Department, University of Oklahoma, USA. Her research interests include power system operation and planning, renewable energy integration, and ancillary services. (e-mail: bianqiaoyan@zju.edu.cn)

Huanhai Xin (M'14) received the Ph. D. degree from Zhejiang University in 2007. He was a postdoctor in the Electrical Engineering and Computer Science Department of the University of Central Florida, Orlando, from June 2009 to July 2010. He is currently a Professor in the Department of Electrical Engineering, Zhejiang University. His research interests include distributed control in active distribution grid and micro-gird, AC/DC power system transient stability analysis and control, and grid-integration of large-scale renewable energy to weak grid. (e-mail: xinhh@zju.edu.cn)

Zhen Wang (M'11) received the B. Eng., M. Eng. and Ph. D. degrees from Xi'an Jiaotong University, Zhejiang University, and Hong Kong Polytechnic University in 1998, 2001, and 2009, respectively. Currently he is a full-time Professor in the Department of Electrical Engineering, Zhejiang University. He was the recipient of 2014 Endeavour Research Fellowship sponsored by Australia Government and visiting scholar of the University of Western Australia from Feb. 2014 to Aug. 2014. His research interests include power system stability and control, renewable energy integration and VSC-HVDC transmission. (e-mail: eezwang@ieee.org)
Corresponding author: Guanzhong Wang, e-mail: 11510002@zju.edu.cn
Received Date: 2015-11-18
Accepted Date: 2016-05-25

Abstract

Abstract

Nowadays, limited predictability and controllability of wind power are regarded as some bottlenecks to wind generation integration with the power system. This paper introduces a robust reserve scheduling method, where the spinning reserve allocation among conventional units is considered as well. The method applies to asymmetrical wind power distribution, and offers control on the degree of solution's conservatism by changing the robustness budget. Meanwhile, distributional information of wind power is represented by mean value and asymmetrical bounds. Furthermore, the model is converted into a deterministic programming problem with dual theory. Case studies for asymmetrically distributed wind power illustrate its effectiveness.
- Power system,
- reserve scheduling,
- robust,
- wind power

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References(32)

References

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A Robust Reserve Scheduling Method Considering Asymmetrical Wind Power Distribution

doi: 10.1109/JAS.2017.7510652

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