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文章摘要
基于量化风电场限功率的电力系统旋转备用优化研究
Spinning reserve optimization in power system under power-limited of the wind farm
Received:February 12, 2020  Revised:February 24, 2020
DOI:10.19753/j.issn1001-1390.2022.01.003
中文关键词: 限功率  旋转备用(SR)  二次调频  量化  粒子群算法
英文关键词: power-limited,spinning reserve, Secondary frequency modulation,quantification,particle swarm optimization
基金项目:国家自然科学基金项目( 51507157);国家电网有限公司华东分部科技项目(SGHD0000DKJS1900414)
Author NameAffiliationE-mail
JIANG Chengcheng* Shanghai University of Engineering Science School of Electrical and Electronic EngineeringShanghai 648368505@qq.com 
lujianyu 1 1@1.com 
WEI Yunbing Shanghai University of Engineering Science School of Electrical and Electronic EngineeringShanghai ee_dmegc@263.net 
ZHU Jianan Shanghai University of Engineering Science School of Electrical and Electronic EngineeringShanghai 798490674@qq.com 
ZHU Chengming Shanghai University of Engineering Science School of Electrical and Electronic EngineeringShanghai 2570455228@qq.com 
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中文摘要:
      提出了基于风电场限功率运行的研究方法,将风电场限功率部分作为特殊的负旋转备用,将可中断负荷作为特殊的正旋转备用,并分析了此研究方法对电网调频产生的影响。采用成本效益分析法建立了系统启停成本、旋转备用调用成本、可中断容量成本、风电场限功率成本、约束违反成本、发电成本之和最小的目标函数。通过限功率值的量化与大小负荷的需求划分出了数个场景,采用基于变异策略的粒子群算法结合蒙特卡洛模拟对模型进行求解,同时考虑到机组组合出力分配,提高了模型的求解精度。最后对各场景计算结果进行分析,验证了所提优化模型的优越性。
英文摘要:
      This paper proposed a research method based on wind farm power-limited operation. The wind farm power-limited part treated as a special negative spinning reserve, and the interruptible load used as a special positive spinning reserve,the influence of this research method on the frequency modulation of the power grid is analyzed. It used the cost-benefit analysis method to establish the objective functions of the system's minimum start-stop cost, spinning reserve call cost, interruptible capacity cost, power-limited cost of the wind farm, constraint violation cost, and generation cost. It divided several scenarios through the quantification of the power-limited value and the demand for large and small loads. And It uses particle swarm optimization based on the mutation strategy combined with Monte Carlo simulation to solve this model. At the same time, considering the unit output distribution, Improved the model's accuracy. Finally, the calculation results of each scenario are analyzed to verify the superiority of the proposed optimization model.
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