Adaptive Iterative Learning Control Technology for Distribution Network Protection Devices
In response to the complex structure of distribution network protection devices,existing control technologies have limitations in convergence of control results and error control.A self-adaptive iterative learning control technology for distribution network protection devices is proposed.Graph theory principles are used to analyze and optimize the design of distribution networks,by decomposing complex distribution network structures and simplifying them into simpler forms.Iterative learning control and a-daptive iterative learning control theory are combined to improve and optimize the protection device of the distribution network.The k-means clustering method is used to partition and integrate data with similar optimal compensation capabilities,and the compensation capacity was adjusted to meet the maximum num-ber of switching constraints.A control model based on the convergence proof function of adaptive iterative learning control is constructed to achieve progressive tracking of distribution network protection devices.The experimental results show that this technology has small error and can effectively iterate learning con-trol for encryption function,protection function,and topology adaptive measurement points.
online decouplingadaptive protection device for distribution networkadaptive iterationlearning control
国家科技期刊平台
NSTL
万方数据
