Yuxuan Zhao^1,2,*, Bo Wang¹, Shu Wang¹, Wenjun Xu², Gang Ma²

Energy Engineering, Vol.121, No.12, pp. 3711-3733, 2024, DOI:10.32604/ee.2024.054032 - 22 November 2024

Abstract The output of photovoltaic power stations is significantly affected by environmental factors, leading to intermittent and fluctuating power generation. With the increasing frequency of extreme weather events due to global warming, photovoltaic power stations may experience drastic reductions in power generation or even complete shutdowns during such conditions. The integration of these stations on a large scale into the power grid could potentially pose challenges to system stability. To address this issue, in this study, we propose a network architecture based on VMD-KELM for predicting the power output of photovoltaic power plants during severe weather… More >

Mohammed A. Alhartomi^1,*, Mohammad F. L. Abdullah², Wafi A. B. Mabrouk², Mohammed S. M. Gismalla³, Ahmed Alzahmi¹, Saeed Alzahrani¹, Mohammad R. Altimania¹, Mohammed S. Alsawat⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.3, pp. 2087-2105, 2024, DOI:10.32604/cmes.2024.055679 - 31 October 2024

Abstract The demand for broadband data services on high-speed trains is rapidly growing as more people commute between their homes and workplaces. However, current radio frequency (RF) technology cannot adequately meet this demand. In order to address the bandwidth constraint, a technique known as free space optics (FSO) has been proposed. This paper presents a mathematical derivation and formulation of curve track G2T-FSO (Ground-to-train Free Space Optical) model, where the track radius characteristics is 2667 m, divergence angle track is 1.5° for train velocity at V = 250 km/h. Multiple transmitter configurations are proposed to maximize More >

Naeem Raza¹, Muhammad Asif Habib¹, Mudassar Ahmad¹, Qaisar Abbas^2,*, Mutlaq B. Aldajani², Muhammad Ahsan Latif³

CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 911-931, 2024, DOI:10.32604/cmc.2024.055049 - 15 October 2024

Abstract Vision-based vehicle detection in adverse weather conditions such as fog, haze, and mist is a challenging research area in the fields of autonomous vehicles, collision avoidance, and Internet of Things (IoT)-enabled edge/fog computing traffic surveillance and monitoring systems. Efficient and cost-effective vehicle detection at high accuracy and speed in foggy weather is essential to avoiding road traffic collisions in real-time. To evaluate vision-based vehicle detection performance in foggy weather conditions, state-of-the-art Vehicle Detection in Adverse Weather Nature (DAWN) and Foggy Driving (FD) datasets are self-annotated using the YOLO LABEL tool and customized to four vehicle… More >

Razieh Keshavarzi, Mehdi Jahangiri^*

Energy Engineering, Vol.121, No.6, pp. 1381-1401, 2024, DOI:10.32604/ee.2024.050029 - 21 May 2024

Abstract Nowadays, the use of renewable energies, especially wind, solar, and biomass, is essential as an effective solution to address global environmental and economic challenges. Therefore, the current study examines the energy-economic-environmental analysis of off-grid electricity generation systems using solar panels, wind turbines, and biomass generators in various weather conditions in Iran. Simulations over 25 years were conducted using HOMER v2.81 software, aiming to determine the potential of each region and find the lowest cost of electricity production per kWh. In the end, to identify the most suitable location, the Technique for Order Preference by Similarity… More > Graphic Abstract

Chenglian Ma¹, Rui Han¹, Zhao An^2,*, Tianyu Hu², Meizhu Jin²

Energy Engineering, Vol.121, No.5, pp. 1245-1261, 2024, DOI:10.32604/ee.2024.046644 - 30 April 2024

Abstract Precise forecasting of solar power is crucial for the development of sustainable energy systems. Contemporary forecasting approaches often fail to adequately consider the crucial role of weather factors in photovoltaic (PV) power generation and encounter issues such as gradient explosion or disappearance when dealing with extensive time-series data. To overcome these challenges, this research presents a cutting-edge, multi-stage forecasting method called D-Informer. This method skillfully merges the differential transformation algorithm with the Informer model, leveraging a detailed array of meteorological variables and historical PV power generation records. The D-Informer model exhibits remarkable superiority over competing… More > Graphic Abstract

Fatemeh Hassani Khorshidi¹, Saeed Kazemi Najafi¹, Farhood Najafi^2,*, Antonio Pizzi^3,*, Dick Sandberg⁴, Rabi Behrooz¹

Journal of Renewable Materials, Vol.12, No.2, pp. 305-323, 2024, DOI:10.32604/jrm.2023.043953 - 11 March 2024

Abstract The purpose of this research study was to investigate the properties of polyurethane coatings based on lignin nano-particles. For this purpose, the prepared coatings were applied to pine wood surfaces and weathered artificially. Subsequently, color and gloss of the coatings were measured before and after the weathering test. Field emission scanning electron microscopy (FE-SEM) micrographs prepared from the coatings showed that the average size of nano-particles in the polyurethane substrate was approximately 500 nm. Nuclear magnetic resonance (¹³C-NMR) spectroscopy showed that strong urethane bonds were formed in the nano-lignin-based polyurethane. Differential calorimetric analysis (DSC) test revealed… More > Graphic Abstract

Hanpeng Kou¹, Tianlong Bu¹, Leer Mao¹, Yihong Jiao^2,*, Chunming Liu²

Energy Engineering, Vol.121, No.4, pp. 1027-1048, 2024, DOI:10.32604/ee.2023.045358 - 26 March 2024

Abstract

In order to play a positive role of decentralised wind power on-grid for voltage stability improvement and loss reduction of distribution network, a multi-objective two-stage decentralised wind power planning method is proposed in the paper, which takes into account the network loss correction for the extreme cold region. Firstly, an electro-thermal model is introduced to reflect the effect of temperature on conductor resistance and to correct the results of active network loss calculation; secondly, a two-stage multi-objective two-stage decentralised wind power siting and capacity allocation and reactive voltage optimisation control model is constructed to take account

… More > Graphic Abstract

Jiahao Zhang, Honglin Wang^*

CMC-Computers, Materials & Continua, Vol.76, No.2, pp. 2427-2441, 2023, DOI:10.32604/cmc.2023.038462 - 30 August 2023

Abstract With the rapid development of technology, processing the explosive growth of meteorological data on traditional standalone computing has become increasingly time-consuming, which cannot meet the demands of scientific research and business. Therefore, this paper proposes the implementation of the parallel Clustering Large Application based upon RANdomized Search (CLARANS) clustering algorithm on the Spark cloud computing platform to cluster China’s climate regions using meteorological data from 1988 to 2018. The aim is to address the challenge of applying clustering algorithms to large datasets. In this paper, the morphological similarity distance is adopted as the similarity measurement… More >

Payal Soni, J. Subhashini^*

Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 1225-1242, 2023, DOI:10.32604/iasc.2023.038155 - 29 April 2023

Abstract In the current context, a smart grid has replaced the conventional grid through intelligent energy management, integration of renewable energy sources (RES) and two-way communication infrastructures from power generation to distribution. Energy management from the distribution side is a critical problem for balancing load demand. A unique energy management strategy (EMS) is being developed for office building equipment. That includes renewable energy integration, automation, and control based on the Artificial Neural Network (ANN) system using Matlab Simulink. This strategy reduces electric power consumption and balances the load demand of the traditional grid. This strategy is More >

R. Surendran^1,*, Youseef Alotaibi², Ahmad F. Subahi³

Computer Systems Science and Engineering, Vol.46, No.3, pp. 3371-3386, 2023, DOI:10.32604/csse.2023.034465 - 03 April 2023

Abstract High precision and reliable wind speed forecasting have become a challenge for meteorologists. Convective events, namely, strong winds, thunderstorms, and tornadoes, along with large hail, are natural calamities that disturb daily life. For accurate prediction of wind speed and overcoming its uncertainty of change, several prediction approaches have been presented over the last few decades. As wind speed series have higher volatility and nonlinearity, it is urgent to present cutting-edge artificial intelligence (AI) technology. In this aspect, this paper presents an intelligent wind speed prediction using chicken swarm optimization with the hybrid deep learning (IWSP-CSODL)… More >