首页|基于RNN的电力负荷波动分析及预测研究

基于RNN的电力负荷波动分析及预测研究

扫码查看
基于ANOVA分析了负荷波动的影响因素,结果表明,最高温度、最低温度、平均温度的P值均小于α,即最高温度、最低温度、平均温度对负荷波动有显著性影响.在此基础上,基于RNN建立了负荷预测模型,通过算例分析验证了模型的有效性.
Analysis and Prediction of Power Load Fluctuation Based on RNN
This paper analyzes the influencing factors of load fluctuation based on ANOVA,and the results show that the P value of the highest temperature,lowest temperature and average temperature are all less than α,that is,the highest temperature,lowest temperature and mean temperature have a significant effect on the load fluctuation.Furthermore,the load prediction model is established based on RNN and the model is verified by example analysis.

one-way variance analysisload fluctuationtemperaturerecurrent neural network

温静

展开 >

国网河南省电力公司洛阳供电公司,河南 洛阳 471000

单因素方差分析 负荷波动 温度 湿度 循环神经网络

2024

电气开关
沈阳电气传动研究所

电气开关

影响因子:0.281
ISSN:1004-289X
年,卷(期):2024.62(5)