Yue He¹, Yaxiong You¹, Zhian He¹, Haiying Lu¹, Lei Chen^2,*, Yuqi Jiang², Hongkun Chen²

Energy Engineering, Vol.121, No.10, pp. 2825-2849, 2024, DOI:10.32604/ee.2024.052371 - 11 September 2024

Abstract In recent times, the impact of typhoon disasters on integrated energy active distribution networks (IEADNs) has received increasing attention, particularly, in terms of effective cascading fault path prediction and enhanced fault recovery performance. In this study, we propose a modified ORNL-PSerc-Alaska (OPA) model based on optimal power flow (OPF) calculation to forecast IEADN cascading fault paths. We first established the topology and operational model of the IEADNs, and the typical fault scenario was chosen according to the component fault probability and information entropy. The modified OPA model consisted of two layers: An upper-layer model to More >

Chen Gu^1,*, Caiyu Wang¹, Mengjiao Du², Kan Yi², Bihong Zhu¹, Hao Wang², Shu Dai¹

The International Conference on Computational & Experimental Engineering and Sciences, Vol.27, No.3, pp. 1-1, 2023, DOI:10.32604/icces.2023.09776

Abstract Site measurement is essential to the meteorological and oceanographic parameters of offshore wind farms. A floating lidar measurement buoy was deployed at a Qingzhou VI wind farm where is 45-80 km away from Guangdong coast. The field observation including wind and wave data start from March, 2021.The lidar wind data is compared and calibrated with the fixed wind tower data for three months, the accuracy meets the standard of stadge3 carbon trust. In this study, all these data are used to recalibrate for the met-ocean model to relies extreme conditions, such as Typhoon Kompasu(2118) and More >

Yingxian Huang, Xueyan Ding, Yanan Zhang, Leiming Yan^*

Journal of Quantum Computing, Vol.4, No.2, pp. 85-95, 2022, DOI:10.32604/jqc.2022.031436 - 16 May 2023

Abstract A GRASP-based algorithm called T_GRASP for avoiding typhoon route optimization is suggested to increase the security and effectiveness of ship navigation. One of the worst natural calamities that can disrupt a ship’s navigation and result in numerous safety mishaps is a typhoon. Currently, the captains manually review the collected weather data and steer clear of typhoons using their navigational expertise. The distribution of heavy winds and waves produced by the typhoon also changes dynamically as a result of the surrounding large-scale air pressure distribution, which significantly enhances the challenge of the captain’s preparation for avoiding… More >

Lina Wang^1,2,*, Xilin Deng¹, Peng Ge¹, Changming Dong^2,3, Brandon J. Bethel³, Leqing Yang¹, Jinyue Xia⁴

CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 2151-2168, 2022, DOI:10.32604/cmc.2022.027415 - 18 May 2022

Abstract Though numerical wave models have been applied widely to significant wave height prediction, they consume massive computing memory and their accuracy needs to be further improved. In this paper, a two-dimensional (2D) significant wave height (SWH) prediction model is established for the South and East China Seas. The proposed model is trained by Wave Watch III (WW3) reanalysis data based on a convolutional neural network, the bi-directional long short-term memory and the attention mechanism (CNN-BiLSTM-Attention). It adopts the convolutional neural network to extract spatial features of original wave height to reduce the redundant information input… More >

Aodi Fu¹, Mingxuan Zhu², Wenzheng Yu^1,*, Xin Yao¹, Hanxiaoya Zhang³

Journal on Big Data, Vol.4, No.1, pp. 77-86, 2022, DOI:10.32604/jbd.2022.027477 - 04 May 2022

Abstract In 2014, Typhoon Rammasun invaded Qinzhou, Guangxi, causing damage to the wind tower sensor at 80 m in Qinzhou. In order to restore the wind speed at 80 m at that time, this paper was based on the hourly average wind speed data of the wind tower and meteorological station from 2017–2019, and constructed the wind speed related model of Meteorological Station and the wind measuring tower in Qinzhou, Moreover, this paper Based on the hourly average wind speed data of Qinzhou Meteorological Station in 2014, Restored the hourly average wind speed of the anemometer tower during More >

Shuai Yuan¹, Guizhi Wang^1,*, Jibo Chen¹, Wei Guo²

Journal on Artificial Intelligence, Vol.1, No.2, pp. 69-88, 2019, DOI:10.32604/jai.2019.06535

Abstract This paper develops a joint model utilizing the principal component analysis (PCA) and the back propagation (BP) neural network model optimized by the Levenberg Marquardt (LM) algorithm, and as an application of the joint model to investigate the damages caused by typhoons for a coastal province, Fujian Province, China in 2005-2015 (latest). First, the PCA is applied to analyze comprehensively the relationship between hazard factors, hazard bearing factors and disaster factors. Then five integrated indices, overall disaster level, typhoon intensity, damaged condition of houses, medical rescue and self-rescue capability, are extracted through the PCA; Finally,… More >