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Generalized load graphical forecasting method based on modal decomposition

Global Energy Interconnection 2024年第2期7卷 166-178页

作者： Lizhen Wu Peixin Chang Wei Chen Tingting Pei College of Electrical and Information Engineering Lanzhou University of TechnologyLanzhou 730050P.R.China School of Electrical Data Engineering University of Technology SydneyNSW2007Australia

In a“low-carbon”context,the power load is affected by the coupling of multiple factors,which gradually evolves from the traditional“pure load”to the generalized load with the dual characteristics of“load+power supply.”Traditional time-series forecasting methods are no longer suitable owing to the complexity and uncertainty associated with generalized loads.From the perspective of image processing,this study proposes a graphical short-term prediction method for generalized loads based on modal decomposition.First,the datasets are normalized and feature-filtered by comparing the results of Xtreme gradient boosting,gradient boosted decision tree,and random forest algorithms.Subsequently,the generalized load data are decomposed into three sets of modalities by modal decomposition,and red,green,and blue(RGB)images are generated using them as the pixel values of the R,G,and B channels.The generated images are diversified,and an optimized DenseNet neural network was used for training and prediction.Finally,the base load,wind power,and photovoltaic power generation data are selected,and the characteristic curves of the generalized load scenarios under different permeabilities of wind power and photovoltaic power generation are obtained using the density-based spatial clustering of applications with noise algorithm.Based on the proposed graphical forecasting method,the feasibility of the generalized load graphical forecasting method is verified by comparing it with the traditional time-series forecasting method.

关键词： Load forecasting Generalized load Image processing DenseNet modal decomposition

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LQR Control Scheme for Active Vehicle Suspension Systems Based on modal decomposition

LQR Control Scheme for Active Vehicle Suspension Systems Bas...

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第25届中国控制与决策会议

作者： Xinjiang Wei Junsheng Li Xiaohua Liu School of Mathematics and Information Ludong University

ISBN: (纸本)9781467355339

A new control scheme combining the classical LQR control with modal decomposition method is presented for an active vehicle suspension system. modal decomposition is proposed to optimize the weighted modal matrix, which gives each modal decomposition components with different weights according to their different importance. The LQR control scheme based on modal decomposition method is designed to improve anti-disturbance performance for the vehicle suspension system. Finally, simulations for a two-degree-of-freedom quarter-car model with an active suspension are given to demonstrate the effectiveness of the proposed approach compared with the passive suspension.

关键词： LQR control modal decomposition robust control active vehicle suspension system

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