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  • Open Access


    Analysis and Assessment of Wind Energy Potential of Almukalla in Yemen

    Murad A. A. Almekhlafi1, Fahd N. Al-Wesabi2,3, Majdy M. Eltahir4, Anwer Mustafa Hilal5, Amin M. El-Kustaban6, Abdelwahed Motwakel5, Ishfaq Yaseen5, Manar Ahmed Hamza5,*

    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3113-3129, 2022, DOI:10.32604/cmc.2022.024355

    Abstract Energy is an essential element for any civilized country's social and economic development, but the use of fossil fuels and nonrenewable energy forms has many negative impacts on the environment and the ecosystem. The Republic of Yemen has very good potential to use renewable energy. Unfortunately, we find few studies on renewable wind energy in Yemen. Given the lack of a similar analysis for the coastal city, this research newly investigates wind energy's potential near the Almukalla area by analyzing wind characteristics. Thus, evaluation, model identification, determination of available energy density, computing the capacity factors for several wind turbines and… More >

  • Open Access


    Design of Neural Network Based Wind Speed Prediction Model Using GWO

    R. Kingsy Grace1,*, R. Manimegalai2

    Computer Systems Science and Engineering, Vol.40, No.2, pp. 593-606, 2022, DOI:10.32604/csse.2022.019240

    Abstract The prediction of wind speed is imperative nowadays due to the increased and effective generation of wind power. Wind power is the clean, free and conservative renewable energy. It is necessary to predict the wind speed, to implement wind power generation. This paper proposes a new model, named WT-GWO-BPNN, by integrating Wavelet Transform (WT), Back Propagation Neural Network (BPNN) and Grey Wolf Optimization (GWO). The wavelet transform is adopted to decompose the original time series data (wind speed) into approximation and detailed band. GWO – BPNN is applied to predict the wind speed. GWO is used to optimize the parameters… More >

  • Open Access


    Analysis and Assessment of Wind Energy Potential of Al-Hodeidah in Yemen

    Fahd N. Al-Wesabi1,2,*, Murad A. Almekhlafi3, Mohammed Abdullah Al-Hagery4, Mohammad Alamgeer5, Khalid Mahmood5, Majdy M. Eltahir5, Ali M. Al-Sharafi2,6, Amin M. El-Kustaban7

    CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 1995-2011, 2021, DOI:10.32604/cmc.2021.018644

    Abstract Renewable energy is one of the essential elements of the social and economic development in any civilized country. The use of fossil fuels and the non-renewable form of energy has many adverse effects on the most of ecosystems. Given the high potential of renewable energy sources in Yemen and the absence of similar studies in the region, this study aimed to examine the wind energy potential of Hodeidah-Yemen Republic by analyzing wind characteristics and assessment, determining the available power density, and calculate the wind energy extracted at different heights. The average wind speed of Hodeidah was obtained only for the… More >

  • Open Access


    Short-term Wind Speed Prediction with a Two-layer Attention-based LSTM

    Jingcheng Qian1, Mingfang Zhu1, Yingnan Zhao2,*, Xiangjian He3

    Computer Systems Science and Engineering, Vol.39, No.2, pp. 197-209, 2021, DOI:10.32604/csse.2021.016911

    Abstract Wind speed prediction is of great importance because it affects the efficiency and stability of power systems with a high proportion of wind power. Temporal-spatial wind speed features contain rich information; however, their use to predict wind speed remains one of the most challenging and less studied areas. This paper investigates the problem of predicting wind speeds for multiple sites using temporal and spatial features and proposes a novel two-layer attention-based long short-term memory (LSTM), termed 2Attn-LSTM, a unified framework of encoder and decoder mechanisms to handle temporal-spatial wind speed data. To eliminate the unevenness of the original wind speed,… More >

  • Open Access


    Resource Assessment of Wind Energy Potential of Mokha in Yemen with Weibull Speed

    Abdulbaset El-Bshah1, Fahd N. Al-Wesabi2,3,*, Ameen M. Al-Kustoban4, Mohammad Alamgeer5, Nadhem Nemri5, Majdy M. Eltahir5, Hany Mahgoub6, Noha Negm7

    CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 1123-1140, 2021, DOI:10.32604/cmc.2021.018427

    Abstract The increasing use of fossil fuels has a significant impact on the environment and ecosystem, which increases the rate of pollution. Given the high potential of renewable energy sources in Yemen and other Arabic countries, and the absence of similar studies in the region. This study aims to examine the potential of wind energy in Mokha region. This was done by analyzing and evaluating wind properties, determining available energy density, calculating wind energy extracted at different altitudes, and then computing the capacity factor for a few wind turbines and determining the best. Weibull speed was verified as the closest to… More >

  • Open Access


    Seasonal Characteristics Analysis and Uncertainty Measurement for Wind Speed Time Series

    Xing Deng1,2, Haijian Shao1,2,*, Xia Wang3,4

    Energy Engineering, Vol.117, No.5, pp. 289-299, 2020, DOI:10.32604/EE.2020.011126

    Abstract Wind speed’s distribution nature such as uncertainty and randomness imposes a challenge in high accuracy forecasting. Based on the energy distribution about the extracted amplitude and associated frequency, the uncertainty measurement is processed through Rényi entropy analysis method with time-frequency nature. Nonparametric statistical method is used to test the randomness of wind speed, more precisely, whether or not the wind speed time series is independent and identically distribution (i.i.d) based on the output probability. Seasonal characteristics of wind speed are analyzed based on self-similarity in periodogram under scales range generated by wavelet transformation to reasonably divide the original dataset and… More >

  • Open Access


    Wind Speed Prediction Modeling Based on the Wavelet Neural Network

    Zhenhua Guo1,2, Lixin Zhang1,*, Xue Hu1, Huanmei Chen2

    Intelligent Automation & Soft Computing, Vol.26, No.3, pp. 625-630, 2020, DOI:10.32604/iasc.2020.013941

    Abstract Wind speed prediction is an important part of the wind farm management and wind power grid connection. Having accurate prediction of short-term wind speed is the basis for predicting wind power. This paper proposes a short-term wind speed prediction strategy based on the wavelet analysis and the multilayer perceptual neural network for the Dabancheng area, in China. Four wavelet neural network models using the Morlet function as the wavelet basis function were developed to forecast short-term wind speed in January, April, July, and October. Predicted wind speed was compared across the four models using the mean square error and regression.… More >

  • Open Access


    AdaBoosting Neural Network for Short-Term Wind Speed Forecasting Based on Seasonal Characteristics Analysis and Lag Space Estimation

    Haijian Shao1, 2, Xing Deng1, 2, *

    CMES-Computer Modeling in Engineering & Sciences, Vol.114, No.3, pp. 277-293, 2018, DOI:10.3970/cmes.2018.114.277

    Abstract High accurary in wind speed forcasting remains hard to achieve due to wind’s random distribution nature and its seasonal characteristics. Randomness, intermittent and nonstationary usually cause the portion problem of the wind speed forecasting. Seasonal characteristics of wind speed means that its feature distribution is inconsistent. This typically results that the persistence of excitation for modeling can not be guaranteed, and may severely reduce the possibilities of high precise forecasting model. In this paper, we proposed two effective solutions to solve the problems caused by the randomness and seasonal characteristics of the wind speed. (1) Wavelet analysis is used to… More >

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