基于模糊识别网络的交直流配电系统发展阶段评价

Shigong Jiang, Hongjun Li, Wei Liu, Jianfeng Yan, Z. Shen, Jun Han
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引用次数: 0

摘要

为了促进可再生能源的利用,满足多交直流负荷的需求,有必要明确交直流配电系统的演进路线和发展形式。模糊神经网络将人工神经网络与模糊识别理论相结合,可以有效地评价模糊问题。首先,构建了交直流配电系统发展阶段评价指标体系。其次,通过选取各指标的参考样本,建立交直流配电系统发展阶段评价的模糊隶属度函数;第三,采用插值方法对参考样本和模糊输出进行插值,建立输入和输出之间的对应关系。最后,将交直流配电系统发展阶段评价问题转化为模糊辨识问题。在充分利用神经网络自组织和自学习能力的基础上,对交直流配电系统的发展阶段进行了评价。以实际交直流配电系统为例,验证了所提指标体系和评价算法的有效性。评价结果可以准确判断交直流配电系统的发展阶段,为网络框架建设和可再生能源消纳提供指导。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Developmental Stage Evaluation of AC/DC Distribution System Based on Fuzzy Recognition Network
In order to promote the consumption of renewable energy and meet the needs of multiple AC/DC load, it is necessary to define the evolution route and development form of AC/DC distribution system. A fuzzy neural network can evaluate fuzzy problems effectively by combining artificial neural network and fuzzy recognition theory. Firstly, the evaluation index system of developmental stage for AC/DC distribution system is constructed. Secondly, the fuzzy membership function of AC/DC distribution system for developmental stage evaluation is established by selecting the reference samples of each indicator. Thirdly, interpolation method is used to interpolate the reference samples and fuzzy output, so as to establish the corresponding relation between input and output. Finally, the developmental stage evaluation problem of AC/DC distribution system is transformed into fuzzy identification problem. On the basis of fully utilize the self-organizing and self-learning ability of neural network, the developmental stage of AC/DC distribution system is evaluated. The effectiveness of proposed index system and evaluation algorithm is verified by taking an actual AC/DC distribution system as an example. The evaluation results can accurately determine the development stage of AC/DC distribution system, and provide guidance for the construction of network framework and the consumption of renewable energy.
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