无刷双馈电机的电磁设计特点-南方电网技术.doc

无刷双馈电机的电磁设计特点-南方电网技术.doc

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无刷双馈电机的电磁设计特点-南方电网技术

文章编号、中图分类号、文献标识码及学科分类号: 考虑电压偏移风险的配电网分布式发电最优协调方法 吴杰康,刘向东,晏浩然,林奕鑫 (广东工业大学自动化学院,广东省 广州市 510006) An optimal coordination Method for distributed generation in distribution networks considering voltage fluctuation risk WU Jie-kang, LIU Xiang-dong,YAN Hao-ran,LIN Yi-xin (School of Automation, Guangdong University of Technology, Guangzhou 510006, Guangdong) ABSTRACT: In allusion to the randomness of output power of distributed generation (DG) and load, a voltage fluctuation risk value calculation and optimization model based on point estimation method and CVaR (Conditional Value at risk) method for distribution network with DG is proposed. The mapping relationship between random variables and objective function can establish by the point estimation method and Cornish-Fisher series. Point estimation method transformed the probability problem into a deterministic problem, then Cornish-Fisher series method transformed the characteristics of the objective function value into a probability distribution, using VaR(Value at risk) method and CVaR (Conditional Value at risk) method to calculate the voltage fluctuation risk index of the node and the system. In addition, this paper takes the minimum risk value of the system voltage fluctuations as the objective function, and adopts the quantum particle swarm optimization algorithm to establish the voltage fluctuation risk optimization model. Taking the IEEE-33 system for example, considering each node access DG, compared the system voltage fluctuation risk before and after the connection of DG, and obtained the optimal combination of output power of distributed power supply through optimization calculation. KEY WORDS:distribution networks; distributed generation; optimal coordination; voltage fluctuation risk; quantum particle swarm optimization 摘要:针对分布式电源和负荷功率的随机性问题,提出基于点估计法和CVaR (Conditional Value at risk)方法的含分布式电源的配电网电压偏移风险值计算与优化模型。通过点估计法和Cornish-Fisher级数可建立随机变量与目标函数之间的映射关系。点估计法将概率问题转化为确定性问题,Cornish-Fisher级数展开则将统计特征值转化为目标函数的概率分布,再

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