首页|基于径向基神经网络的分布式光伏调控系统设计

基于径向基神经网络的分布式光伏调控系统设计

扫码查看
随着光伏能源在电力系统中的普及,高比例的光伏接入给配电网带来了电压波动、潮流倒送等一系列挑战.为了解决高比例的光伏接入导致的配电网的电压波动、潮流倒送等问题,研究利用径向基神经网络实现光伏配电网络的全局最优逼近,并对其进行了一系列改进,设计出一种新的分布式光伏调控系统.实验结果显示,专家们对系统的性能指标评价较高,其中预测精度、调控速度、稳定性平均得分达到了 88.1、85.3、84.4.研究提出的光伏调控系统具有调节精度高,稳定性好等优点,具有重要的理论意义和应用价值.
Design of Distributed Photovoltaic Control System Based on Radial Basis Function Neural Network
With the popularization of photovoltaic energy in the power system,the high proportion of photovoltaic integration has brought a series of challenges to the distribution network,such as voltage fluctuations and power flow reversal.In order to solve these problems,such as voltage fluctuations and power flow backflow caused by high proportion of photovoltaic access in the distribution network,a radial basis function neural network was studied to achieve global optimal approximation of the photovoltaic distribution network,and a series of improvements were made to design a new distributed photovoltaic control system.The experimental results show that experts have high evaluations of the system's performance indicators,with average scores of 88.1,85.3,and 84.4 for pre-diction accuracy,control speed,and stability.The proposed photovoltaic regulation system has the advantages of high regulation accu-racy and good stability,and has important theoretical significance and application value.

RBFparameter optimizationDOWAregulatory system

郭亮、梁桦

展开 >

湖南电子科技职业学院,长沙 410000

RBF 参数优化 DOWA 调控系统

2024

自动化与仪器仪表
重庆工业自动化仪表研究所,重庆市自动化与仪器仪表学会

自动化与仪器仪表

CSTPCD
影响因子:0.327
ISSN:1001-9227
年,卷(期):2024.(11)