[1]薛金花,王德顺,郁正纲,等.基于风电可调节不确定代价的风光柴储联合优化调度[J].郑州大学学报(工学版),2019,40(05):72-78.[doi:10.13705/j.issn.1671-6833.2019.05.006]
 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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基于风电可调节不确定代价的风光柴储联合优化调度()
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《郑州大学学报(工学版)》[ISSN:1671-6833/CN:41-1339/T]

卷:
40卷
期数:
2019年05期
页码:
72-78
栏目:
出版日期:
2019-10-23

文章信息/Info

Title:
Combined Optimal Scheduling of Wind, Diesel and Storage Based on Adjustable Uncertain Cost of Wind Power
作者:
薛金花王德顺郁正纲李红朱信舜窦春霞
中国电力科学研究院有限公司,江苏南京210009; 国网江苏省电力有限公司连云港供电分公司, 江苏连云港222000;南京南瑞继保工程技术有限公司,江苏南京210009; 南京邮电大学先进技术 研究院,江苏南京210023
Author(s):
Xue Jinhua 1Wang Deshun 1Yu Zhenggang 2Li Hong 2Zhu Xinshun 3Dou Chunxia 4
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
关键词:
孤岛微电网不确定代价蓄电池储能系统优化调度粒子群算法
Keywords:
Island microgridUncertain costBattery energy storage systemoptimize schedulingParticle swarm algorithm
DOI:
10.13705/j.issn.1671-6833.2019.05.006
文献标志码:
A
摘要:
针对孤岛微电网中间歇式能源出力的不确定性问题,基于可调节风电的不确定代价,考虑蓄电 池储能系统和柴油发电机组的控制特性.在系统稳定供电的前提下,以系统运维成本、污染物排放量为 目标,引入可调负荷充放电等相关约束,建立孤岛微电网能量优化调度模型,优化储能充放电与柴油机 组出力.并在此基础上,利用改进粒子群算法对模型进行求解,根据所建模型三种情景对比,进一步分析 9个不同调度区间系数对调度结果的影响机理,算例仿真验证了可调节风电不确定代价优化模型和优 化方法的有效性和可行性.
Abstract:
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.
更新日期/Last Update: 2019-10-26