Shaoxiong Wu¹, Ruoxin Li¹, Xiaofeng Tao¹, Hailong Wu^1,*, Ping Miao¹, Yang Lu¹, Yanyan Lu¹, Qi Liu², Li Pan²

CMC-Computers, Materials & Continua, Vol.81, No.2, pp. 3063-3077, 2024, DOI:10.32604/cmc.2024.055381 - 18 November 2024

Abstract Time series prediction has always been an important problem in the field of machine learning. Among them, power load forecasting plays a crucial role in identifying the behavior of photovoltaic power plants and regulating their control strategies. Traditional power load forecasting often has poor feature extraction performance for long time series. In this paper, a new deep learning framework Residual Stacked Temporal Long Short-Term Memory (RST-LSTM) is proposed, which combines wavelet decomposition and time convolutional memory network to solve the problem of feature extraction for long sequences. The network framework of RST-LSTM consists of two More >

Bo Yang^1,*, Yucun Qian¹, Jianzhong Xu², Yaxing Ren³, Yixuan Chen⁴

Energy Engineering, Vol.121, No.8, pp. 2085-2091, 2024, DOI:10.32604/ee.2024.050083 - 19 July 2024

Abstract This article has no abstract. More >

Shunyi Zhao^1,*, Xiaoli Luan¹, Jinfeng Liu², Ruomu Tan³

CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.1, pp. 1-3, 2023, DOI:10.32604/cmes.2022.024993 - 29 September 2022

Abstract This article has no abstract. More >

Wentao Liu, Junxia Ma, Weili Xiong^*

CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.2, pp. 873-892, 2023, DOI:10.32604/cmes.2022.020565 - 31 August 2022

Abstract This paper studies the parameter estimation problems of the nonlinear systems described by the bilinear state space models in the presence of disturbances. A bilinear state observer is designed for deriving identification algorithms to estimate the state variables using the input-output data. Based on the bilinear state observer, a novel gradient iterative algorithm is derived for estimating the parameters of the bilinear systems by means of the continuous mixed p-norm cost function. The gain at each iterative step adapts to the data quality so that the algorithm has good robustness to the noise disturbance. Furthermore, to More >

Ziwei Jiang¹, Shuaibing Li^1,*, Xiping Ma², Xingmin Li², Yongqiang Kang¹, Hongwei Li³, Haiying Dong¹

CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.1, pp. 295-317, 2022, DOI:10.32604/cmes.2022.019996 - 02 June 2022

Abstract

The development and utilization of large-scale distributed power generation and the increase of impact loads represented by electric locomotives and new energy electric vehicles have brought great challenges to the stable operation of the regional power grid. To improve the prediction accuracy of power systems with source-load two-terminal uncertainties, an adaptive cubature Kalman filter algorithm based on improved initial noise covariance matrix Q0 is proposed in this paper. In the algorithm, the Q0 is used to offset the modeling error, and solves the problem of large voltage amplitude and phase fluctuation of the source-load two-terminal uncertain systems.

More >

Min Liu^*

Energy Engineering, Vol.119, No.2, pp. 781-800, 2022, DOI:10.32604/ee.2022.016657 - 24 January 2022

Abstract With the application of phasor measurement units (PMU) in the distribution system, it is expected that the performance of the distribution system state estimation can be improved obviously with the PMU measurements into consideration. How to appropriately place the PMUs in the distribution is therefore become an important issue due to the economical consideration. According to the concept of efficient frontier, a value-at-risk based approach is proposed to make optimal placement of PMU taking account of the uncertainty of measure errors, statistical characteristics of the pseudo measurements, and reliability of the measurement instrument. The reasonability More >

Yonghua Zhou¹, Xun Yang¹, Chao Mi¹

CMES-Computer Modeling in Engineering & Sciences, Vol.89, No.6, pp. 497-512, 2012, DOI:10.3970/cmes.2012.089.497

Abstract The movements of vehicles equipped with various positioning systems such as global and wireless positioning ones have provided beneficial channels to acquire abundant traffic flow information for total road network. However, not all vehicles are mounted with positioning systems and not all equipped positioning facilities are always active. This paper will address how to estimate the number and the states of unequipped vehicles through a series of observations on equipped ones. The proposed estimation process initiates employing the non-analytical microscopic traffic model for particle filter to estimate the number, positions and speeds of unequipped vehicles… More >

S.Mohanty¹, A. Chattopadhyay², J. Wei³, P. Peralta⁴

Structural Durability & Health Monitoring, Vol.5, No.3, pp. 227-250, 2009, DOI:10.3970/sdhm.2009.005.227

Abstract This paper proposes unsupervised system identification based methods to estimate time-series fatigue damage states in real-time. Ultrasound broadband input is used for active damage interrogation. Novel damage index estimation techniques based on dual sensor signals are proposed. The dual sensor configuration is used to remove electrical noise, as well as to improve spatial resolution in damage state estimation. The scalar damage index at any particular damage condition is evaluated using nonparametric system identification techniques, which includes an empirical transfer function estimation approach and a correlation analysis approach. In addition, the effectiveness of two sensor configurations More >

S.Mohanty¹, A. Chattopadhyay², J. Wei³, P. Peralta⁴

Structural Durability & Health Monitoring, Vol.5, No.1, pp. 33-56, 2009, DOI:10.3970/sdhm.2009.005.033

Abstract The current state of the art in the area of real time structural health monitoring techniques offers adaptive damage state prediction and residual useful life assessment. The present paper discusses the use of an integrated prognosis model, which combines an on-line state estimation model with an off-line predictive model to adaptively estimate the residual useful life of an Al-6061 cruciform specimen under biaxial loading. The overall fatigue process is assumed to be a slow time scale process compared to the time scale at which, the sensor signals were acquired for on-line state estimation. The on-line… More >