摘要
随着社会经济的不断发展,电力网络的优化配置已成为关乎各种国计民生的重要因素。针对这些需求,引入电气工程自动化的方法与技术,基于神经网络、模糊PID的优势方法进行优化融合,构建全新的基于模糊神经网络的PID控制算法,并利用仿真实验进行验证。实验结果表明:从恒定、变相两个类型来看,基于模糊神经网络的PID神经网络算法都有明显的学习能力和参数优化能力,且对电力机器控制的误差相比传统PID误差及相对波动较小,能够有效地提升输配电系统中的控制精度,能有效地进行输配电系统优化与应用。
With the continuous development of the social economy,the optimized configuration of the power network has become an important factor related to various national economy and people′s livelihood.In response to these needs,this article introduces methods and technologies of electrical engineering automation,optimizes and integrates the advantages of neural networks and fuzzy PID methods,constructs a new fuzzy neural network PID control algorithm,and conducts simulation experiments.The experimental results show that the fuzzy neural network PID control algorithm has significant learning ability and parameter optimization ability under both constant load and disguised load types,and the error and relative fluctuation of power machine control are smaller compared to traditional PID.It can effectively improve the control accuracy in the transmission and distribution system,and can effectively optimize and apply the transmission and distribution system.
作者
李强
LI Qiang(Gaoyou Branch Jiangsu Yangzhou Sanxin Power Supply Service Co.,Ltd.,Gaoyou 225600,China)
出处
《电气开关》
2025年第4期86-90,共5页
Electric Switchgear
关键词
电气工程自动化
恒定负载
仿真模拟
electrical engineering automation
constant load
analogue simulation
