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  • Open Access


    Assessment Framework of Green Intelligent Transformation of Small Hydropower in China

    Jun Shi*

    Energy Engineering, Vol.119, No.2, pp. 681-697, 2022, DOI:10.32604/ee.2022.014942

    Abstract With the comprehensive promoted construction of the establishment of green small hydropower, the defects of existing small hydropower station are gradually emerging, and it is necessary to implement green intelligent transformation to promote the construction of energy internet in China. This study focuses on constructing a green intelligent planning and transforming assessment framework, and assists management department to filtrate the small hydropower stations which can be transformed reasonably. Firstly, power station economy, ecological environment, technical safety management and social benefits are involved in the assessment index system. Secondly, multi-expert judgment aggregation based on fuzzed comparison scale is put forward to… More >

  • Open Access


    Numerical Study on the Blade Channel Vorticity in a Francis Turbine

    Zhiqi Zhou*

    FDMP-Fluid Dynamics & Materials Processing, Vol.17, No.6, pp. 1091-1100, 2021, DOI:10.32604/fdmp.2021.016618

    Abstract A relevant way to promote the sustainable development of energy is to use hydropower. Related systems heavily rely on the use of turbines, which require careful analysis and optimization. In the present study a mixed experimental-numerical approach is implemented to investigate the related mixed water flow. In particular, particle image velocimetry (PIV) is initially used to verify the effectiveness of the numerical model. Then numerical results are produced for various conditions. It is shown that an increase in the guide vane opening can reduce the extension of the region where the fluid velocity is 0 at the inlet of the… More >

  • Open Access


    A Novel Hybrid Intelligent Prediction Model for Valley Deformation: A Case Study in Xiluodu Reservoir Region, China

    Mengcheng Sun1,2, Weiya Xu1,2,*, Huanling Wang1,3, Qingxiang Meng1,2, Long Yan1,2, Wei-Chau Xie4

    CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 1057-1074, 2021, DOI:10.32604/cmc.2020.012537

    Abstract The narrowing deformation of reservoir valley during the initial operation period threatens the long-term safety of the dam, and an accurate prediction of valley deformation (VD) remains a challenging part of risk mitigation. In order to enhance the accuracy of VD prediction, a novel hybrid model combining Ensemble empirical mode decomposition based interval threshold denoising (EEMD-ITD), Differential evolutions—Shuffled frog leaping algorithm (DE-SFLA) and Least squares support vector machine (LSSVM) is proposed. The non-stationary VD series is firstly decomposed into several stationary subseries by EEMD; then, ITD is applied for redundant information denoising on special sub-series, and the denoised deformation is… More >

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