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作 者:刘金生 程维杰 陈择栖 张俊芳[2] 朱肖镕 柳伟 任祖怡[3] Liu Jinsheng;Cheng Weijie;Chen Zeqi;Zhang Junfang;Zhu Xiaorong;Liu Wei;Ren Zuyi(Shenzhen Power Supply Bureau Co.,Ltd.,Shenzhen 518000,China;School of Automation,Nanjing University of Science and Technology,Nanjing 210094,China;Nanjing NR Electric Co.,Ltd.,Nanjing 211102,China)
机构地区:[1]深圳供电局有限公司,广东深圳518000 [2]南京理工大学自动化学院,江苏南京210094 [3]南京南瑞继保电气有限公司,江苏南京211102
出 处:《南京理工大学学报》2019年第6期684-692,共9页Journal of Nanjing University of Science and Technology
摘 要:为了提高评估准确度,本文提出基于非线性有源自回归(NARX)动态神经网络的孤网自治运行能力综合评估方法。在分析网源荷协调机理的基础上,明确影响孤网自治运行能力的关键因素,包括源源互补、源网协调、源荷协调、网荷互动4个方面。在计及多项关键影响因素的基础上,构建1套可评估孤网自治运行能力的指标体系。使用改进灰关联度分析算法与熵值法对神经网络训练样本进行数据处理分析,以设置NARX神经网络模型。采用基于NARX的孤网自治运行能力综合评估方法进行评估,并利用标准化方法量化评估结果。以某地区典型电网为例,证明该文方法与灰关联度分析方法相比,输出值更贴近目标输出值。A comprehensive evaluation method of autonomous operation capability of an isolated network is proposed based on the nonlinear auto-regression with exogenous(NARX)dynamic neural network to improve the evaluation accuracy.Based on analyzing the mechanism of network-source-load coordination,the key factors affecting the autonomous operation capability of the isolated network are defined,including four aspects:source-source complementation,source-net coordination,source-load coordination and network-load interaction.Considering several key influencing factors,an indicator system is established to evaluate the autonomous operation capability of the isolated network.Training samples of a neural network are processed and analyzed by using improved grey relational degree analysis method and entropy method,and a NARX neural network model is set.The NARX is used to achieve the evaluation and scoring of the autonomous operation capability of the isolated network,and standardized method is used to quantify the evaluating result.Taking a typical power grid in a given area for example,the results show that compared with the gray relation analysis method,the output of this method is closer to the target output.
关 键 词:非线性有源自回归 神经网络 孤网 自治运行 源荷协调 改进灰关联度分析算法 熵值法 标准化方法
分 类 号:TM714.3[电气工程—电力系统及自动化]
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