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Appl. Sci. 2017, 7(7), 680; doi:10.3390/app7070680

Robust Co-Optimization to Energy and Reserve Joint Dispatch Considering Wind Power Generation and Zonal Reserve Constraints in Real-Time Electricity Markets

1
Department of Electrical Engineering, Shenyang University of Technology, Shenyang 110870, Liaoning, China
2
State Key Laboratory of Electrical Insulation and Power Equipment, Xi’an Jiaotong University, Xi’an 710049, Shaanxi, China
3
Department of Electrical Engineering, China Agricultural University, Beijing 100083, China
*
Author to whom correspondence should be addressed.
Academic Editor: Josep M. Guerrero
Received: 10 April 2017 / Revised: 13 May 2017 / Accepted: 7 June 2017 / Published: 1 July 2017
(This article belongs to the Section Energy)
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Abstract

This paper proposes an energy and reserve joint dispatch model based on a robust optimization approach in real-time electricity markets, considering wind power generation uncertainties as well as zonal reserve constraints under both normal and N-1 contingency conditions. In the proposed model, the operating reserves are classified as regulating reserve and spinning reserve according to the response performance. More specifically, the regulating reserve is usually utilized to reduce the gap due to forecasting errors, while the spinning reserve is commonly adopted to enhance the ability for N-1 contingencies. Since the transmission bottlenecks may inhibit the deliverability of reserve, the zonal placement of spinning reserve is considered in this paper to improve the reserve deliverability under the contingencies. Numerical results on the IEEE 118-bus test system show the effectiveness of the proposed model. View Full-Text
Keywords: robust optimization; zonal reserve; joint dispatch; wind power; active set method robust optimization; zonal reserve; joint dispatch; wind power; active set method
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Li, C.; Yun, J.; Ding, T.; Liu, F.; Ju, Y.; Yuan, S. Robust Co-Optimization to Energy and Reserve Joint Dispatch Considering Wind Power Generation and Zonal Reserve Constraints in Real-Time Electricity Markets. Appl. Sci. 2017, 7, 680.

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