Xinwei Wang^1,2,*, Ming Li¹, Hankun Bing¹, Dongxing Zhang¹, Yuanshu Zhang¹

Energy Engineering, Vol.121, No.12, pp. 3875-3898, 2024, DOI:10.32604/ee.2024.056237 - 22 November 2024

Abstract After long-term operation, the performance of components in the GTCC system deteriorates and requires timely maintenance. Due to the inability to directly measure the degree of component malfunction, it is necessary to use advanced exergy analysis diagnosis methods to characterize the components’ health condition (degree of malfunction) through operation data of the GTCC system. The dissipative temperature is used to describe the degree of malfunction of different components in the GTCC system, and an advanced exergy analysis diagnostic method is used to establish a database of overall operating condition component malfunctions in the GTCC system.… More >

Weiru Wang¹, Yulong Cao^1,*, Yanxu Wang¹, Jiale You¹, Guangnan Zhang¹, Yu Xiao²

Energy Engineering, Vol.121, No.12, pp. 3801-3823, 2024, DOI:10.32604/ee.2024.055398 - 22 November 2024

Abstract To ensure frequency stability in power systems with high wind penetration, the doubly-fed induction generator (DFIG) is often used with the frequency fast response control (FFRC) to participate in frequency response. However, a certain output power suppression amount (OPSA) is generated during frequency support, resulting in the frequency modulation (FM) capability of DFIG not being fully utilised, and the system’s unbalanced power will be increased during speed recovery, resulting in a second frequency drop (SFD) in the system. Firstly, the frequency response characteristics of the power system with DFIG containing FFRC are analysed. Then, based… More >

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 >

Vladimir Konovalov^*

FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.11, pp. 2541-2563, 2024, DOI:10.32604/fdmp.2024.051219 - 28 October 2024

Abstract The regime of horizontal subcooled film boiling is characterized by the formation of a thin layer of vapor covering the surface of a flat horizontal heater. Based on the equations of motion of a viscous incompressible fluid and the equation of heat transfer, the stability of such a vapor film is investigated. The influence of the modulation of the gravity field caused by vertical vibrations of the heater of finite frequency, as well as a constant electric field applied normal to the surface of the heater, is taken into account. It is shown that in… More >

Jingbin Wu^1,*, Hongming Yang², Sheng Xiang²

Energy Engineering, Vol.121, No.11, pp. 3263-3287, 2024, DOI:10.32604/ee.2024.054019 - 21 October 2024

Abstract Currently, the operational performance assessment system in the power market primarily focuses on power generation and electricity retail companies, lacking a system tailored to the operational characteristics of power generation/selling integrated companies. Therefore, this article proposes an assessment index system for assessing the operational performance of a power generation/selling integrated company, encompassing three dimensions: basic capacity, development potential, and external environment. A dynamic proportional adjustment coefficient is designed, along with a subjective and objective weighting model for assessment indexes based on a combined weighting method. Subsequently, the operational performance of an integrated company is assessed More > Graphic Abstract

Jingjing Bai¹, Yunpeng Cheng¹, Shenyun Yao^2,*, Fan Wu¹, Cheng Chen¹

Energy Engineering, Vol.121, No.11, pp. 3381-3400, 2024, DOI:10.32604/ee.2024.053683 - 21 October 2024

Abstract To mitigate the impact of wind power volatility on power system scheduling, this paper adopts the wind-storage combined unit to improve the dispatchability of wind energy. And a three-level optimal scheduling and power allocation strategy is proposed for the system containing the wind-storage combined unit. The strategy takes smoothing power output as the main objectives. The first level is the wind-storage joint scheduling, and the second and third levels carry out the unit combination optimization of thermal power and the power allocation of wind power cluster (WPC), respectively, according to the scheduling power of WPC and… More >

Abdul Moiz¹, Malik Shahzaib¹, Abdul Ghafoor Memon¹, Laveet Kumar², Mamdouh El Haj Assad^3,*

Energy Engineering, Vol.121, No.11, pp. 3095-3120, 2024, DOI:10.32604/ee.2024.051214 - 21 October 2024

Abstract To meet the escalating electricity demand and rising fuel costs, along with notable losses in power transmission, exploring alternative solutions is imperative. Gas turbines demonstrate high efficiency under ideal International Organization for Standardization (ISO) conditions but face challenges during summer when ambient temperatures reach 40°C. To enhance performance, the proposal suggests cooling inlet air by 15°C using a vapor absorption chiller (VAC), utilizing residual exhaust gases from a combined cycle power plant (CCPP) to maximize power output. Additionally, diverting a portion of exhaust gases to drive an organic Rankine cycle (ORC) for supplementary power generation… More >

Jyun-Guo Wang^*

Computer Systems Science and Engineering, Vol.48, No.5, pp. 1149-1170, 2024, DOI:10.32604/csse.2024.052931 - 13 September 2024

Abstract In many Eastern and Western countries, falling birth rates have led to the gradual aging of society. Older adults are often left alone at home or live in a long-term care center, which results in them being susceptible to unsafe events (such as falls) that can have disastrous consequences. However, automatically detecting falls from video data is challenging, and automatic fall detection methods usually require large volumes of training data, which can be difficult to acquire. To address this problem, video kinematic data can be used as training data, thereby avoiding the requirement of creating… More >

Pawat Chunhachatrachai^1,*, Chyi-Yeu Lin^1,2

Intelligent Automation & Soft Computing, Vol.39, No.4, pp. 599-618, 2024, DOI:10.32604/iasc.2024.055385 - 06 September 2024

Abstract Angle detection is a crucial aspect of industrial automation, ensuring precise alignment and orientation of components in manufacturing processes. Despite the widespread application of computer vision in industrial settings, angle detection remains an underexplored domain, with limited integration into production lines. This paper addresses the need for automated angle detection in industrial environments by presenting a methodology that eliminates training time and higher computation cost on Graphics Processing Unit (GPU) from machine learning in computer vision (e.g., Convolutional Neural Networks (CNN)). Our approach leverages advanced image processing techniques and a strategic combination of algorithms, including More >

Sana Rezig^*, Foued Khoffi, Mounir Jaouadi, Asma Eloudiani, Slah Msahli

Journal of Renewable Materials, Vol.12, No.6, pp. 1071-1086, 2024, DOI:10.32604/jrm.2024.049935 - 02 August 2024

Abstract Plant derived natural fibers have been widely investigated as alternatives to synthetic fibers in reinforcing polymers. Researchers over the years have explored many plant fibers using different extraction processes to study their physical, chemical, and mechanical properties. In this context, the present study relates to the extraction, characterization, and optimization of Typha angustata L. stem fibers. For this purpose, desirability functions and response surface methodology were applied to simultaneously optimize the diameter (D), linear density (LD); yield (Y), lignin fraction (L), and tenacity (T) of Typha stem fibers. Typha stems have been subjected to both alkali (NaOH) and enzymatic… More > Graphic Abstract