On the Nile Fan's Wave Power Potential and Controlling Factors Integrating Spectral and Geostatistical Techniques

A. Masoud
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Abstract

Wave energy is foreseen to contribute to the 20 % renewable energy supply of Egypt’s electricity budget to meet burgeoning energy demand. This research analyses the Nile Fan wave energy forcasted from numerical modeling for 2020 of the Copernicus Marine Environment Monitoring Service (CMEMS) database, hourly sampled at 0.042° as the finest remotely-sensed data available. Wave power spatial distribution is analyzed using data from 259 points proposed as Wave Energy Converters (WECs). Spectral analyses techniques were appraised for disclosing the frequency and power return periods of the significant wave height and peak periods and to understand the similarity among selected WECs of varied conditions. K-means clustering was used to distinguish energy classes with large inter-class variances. The obtained wave power resources ( av . 5.32 kW/m; maximum of 112.9 kW/m; annual mean of 46.96 MW/m) are among the largest found in the Mediterranean Sea. More than 98 % of the wave power variance is controlled, in decreasing order of influence, by the depth, distance to shore, significant wave height, wave peak period, and the wave principal direction. Deepest water and near shore classes attained the largest wave power. Detailed environmental factors induced the wave shape and power is concluded.
结合波谱和地统计技术研究尼罗河扇的波浪能势及其控制因素
波浪能预计将为埃及电力预算中20%的可再生能源供应做出贡献,以满足迅速增长的能源需求。本研究分析了哥白尼海洋环境监测服务(CMEMS)数据库的数值模拟预测的2020年尼罗河扇波能量,每小时在0.042°采样,作为最精细的遥感数据。利用波浪能转换器(WECs)的259个点的数据分析了波浪能的空间分布。对频谱分析技术进行了评价,以揭示显著波高和峰值周期的频率和功率返回周期,并了解不同条件下选定的白电鳗之间的相似性。K-means聚类用于区分类间方差较大的能量类别。获得的波浪能资源(av。5.32千瓦/ m;最高可达112.9 kW/m;年平均为46.96兆瓦/米)是地中海发现的最大的。超过98%的波浪能变化由深度、到岸距离、有效波高、波浪峰值周期和波浪主方向的影响降序控制。最深的水域和近岸级别获得最大的波浪力。详细总结了影响波浪形态和功率的环境因素。
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