An economic dispatch model in an industrial microgrid with wind power based on robust optimization

被引：0

作者：

Ding, Hao ^{[1
]}

Gao, Feng ^{[1
]}

Liu, Kun ^{[1
]}

Guan, Xiaohong ^{[2
]}

Wu, Jiang ^{[2
]}

机构：

[1] State Key Laboratory for Manufacturing Systems Engineering, Xi'an Jiaotong University, Xi'an

[2] Ministry of Education Key Lab. for Intelligent Networks and Networks Security, Xi'an Jiaotong University, Xi'an

来源：

Dianli Xitong Zidonghua/Automation of Electric Power Systems | 2015年 / 39卷 / 17期

基金：

中国国家自然科学基金;

关键词：

Economic dispatch; Microgrid; Robust optimization; Wind power;

D O I：

10.7500/AEPS20140320002

中图分类号：

学科分类号：

摘要：

Wind power is a kind of new, clean, renewable and widely used energy. Utilizing wind power in an industrial microgrid is of great significance in energy conservation and emission reduction. This paper researches on an industrial microgrid with wind power, establishes a multi-stage model with self-generation scheduling optimation for an industrial microgrid, which aims at minimizing the energy costs through adjusting the production and power generation schedule properly based on robust optimization, and then utilizes Benders decomposition algorithm to solve the model. Numerical tests on the model are given with data of an industrial microgrid, and it is confirmed that the fluctuation of wind power and load is smoothed by the model effectively and the electric energy costs are decreased. Additionally, the model is proved to perform better than the deterministic optimal model under the worst condition, and the balance of conservatism and optimality can be adjusted by different uncertainty prices according to the requirement. ©2015 Automation of Electric Power Systems Press

引用

页码：160 / 167

页数：7

共 13 条

[11]

Deng P., Liu Y., Bi Y., Et al., Survey on robust linear optimization, Control and Decision, 24, 8, pp. 1121-1125, (2009)

[12]

Bertsimas D., Sim M., The price of robustness, Operations Research, 52, 1, pp. 35-53, (2004)

[13]

Wang Y., Zhang J., Wen B., Et al., An optimal neighborhood in phase space based local prediction method for ultra-short-term wind speed forecasting, Automation of Electric Power Systems, 35, 24, pp. 39-43, (2011)

← 1 2 →