[1]Xue Jinhua,Wang Deshun,Yu Zhenggang,et al.Combined Optimal Scheduling of Wind, Diesel and Storage Based on Adjustable Uncertain Cost of Wind Power[J].Journal of Zhengzhou University (Engineering Science),2019,40(05):72-78.[doi:10.13705/j.issn.1671-6833.2019.05.006]
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Journal of Zhengzhou University (Engineering Science)[ISSN
1671-6833/CN
41-1339/T] Volume:
40
Number of periods:
2019 05
Page number:
72-78
Column:
Public date:
2019-10-23
- Title:
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Combined Optimal Scheduling of Wind, Diesel and Storage Based on Adjustable Uncertain Cost of Wind Power
- Author(s):
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Xue Jinhua 1; Wang Deshun 1; Yu Zhenggang 2; Li Hong 2; Zhu Xinshun 3; Dou Chunxia 4
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1. China Electric Power Research Institute Co., Ltd.; 2. Lianyungang Power Supply Branch of State Grid Jiangsu Electric Power Co., Ltd.; 3. Nanjing Narui Relay Engineering Technology Co., Ltd.; 4. Advanced Technology Research Institute of Nanjing University of Posts and Telecommunications
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- Keywords:
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Island microgrid; Uncertain cost; Battery energy storage system; optimize scheduling; Particle swarm algorithm
- CLC:
-
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- DOI:
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10.13705/j.issn.1671-6833.2019.05.006
- Abstract:
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To deal with the uncertainty of intermittent energy in the island microgrid model, based on the uncertain cost of adjustable wind power, this paper enemined the different control characteristics of battery energy storage system and diesel generator set, on the premise of ensuring stable power supply of the system, the optimized charge and discharge of energy storage and diesel unit output. And it introduced the adjustable load and other related constraints with the system cost and pollutant emission as the goal, and established the energy optimization scheduling model of the island microgrid. The related constraints such as adjustable load were introduced to establish an energy optimization scheduling model for the island microgrid. On this basis, the improved particle swarm optimization algorithm was used to solve the model. According to the comparative analysis of the micro-grid system optimization models under three different scenarios, the influence mechanism of nine different scheduling interval coefficients on the scheduling results was further analyzed. The effectiveness and feasibility of the wind turbine uncertain cost optimization model and optimization method were verified by case study.