| 1 | Wind Power Prediction Based on Variational Mode Decomposition and Feature Selection显示文摘Accurate wind power prediction can scientifically arrange wind power output and timely adjust power system dispatching plans. Wind power is associated with its uncertainty,multi-frequency and nonlinearity for it is susceptible to climatic factors such as temperature, air pressure and wind speed.Therefore, this paper proposes a wind power prediction model combining multi-frequency combination and feature selection.Firstly, the variational mode decomposition(VMD) is used to decompose the wind power data, and the sub-components with different fluctuation characteristics are obtained and divided into high-, intermediate-, and low-frequency components according to their fluctuation characteristics. Then, a feature set including historical data of wind power and meteorological factors is established, which chooses the feature sets of each component by using the max-relevance and min-redundancy(m RMR) feature selection method based on mutual information selected from the above set. Each component and its corresponding feature set are used as an input set for prediction afterwards. Thereafter, the high-frequency input set is predicted using back propagation neural network(BPNN), and the intermediate-and low-frequency input sets are predicted using least squares support vector machine(LS-SVM). After obtaining the prediction results of each component, BPNN is used for integration to obtain the final predicted value of wind power, and the ramping rate is verified. Finally, through the comparison, it is found that the proposed model has higher prediction accuracy. | Gang Zhang Benben Xu Hongchi Liu Jinwang Hou Jiangbin Zhang | 2021 | Journal of Modern Power Systems and Clean Energy2021，9，6： | 0 |
| 2 | Optical properties of chain-like soot with water coatings显示文摘In a moist atmosphere,the ageing process of aerosol can make the agglomerated soot particles compact,and cause them to be covered by a water coating.Based on the cluster‒cluster aggregation(CCA)algorithm,the models of chain-like soot with water coatings(Models A to E)were generated in this study.The superposition T-matrix method was employed to calculate their optical properties at 337,550,860,and 1060 nm wavelengths,with a focus on the impact of the soot inclusion morphology and water coating.Our results indicate that for particles with a looser soot-inclusion structure,there is a larger difference in the scattering phase function between them and the corresponding particles with a spherical soot core.The largest relative difference reached 51.8%at 337 nm.Impacted by the size parameter,the extinction cross section(Cext),absorption cross section(Cabs),scattering cross section(Csca),and single scattering albedo(SSA)increased as the water coating radius(Rwater)increased and incidence wavelength decreased.The traditional assumption of a spherical soot core can cause the Cext,Cabs,and Csca to be overestimated,and cause the SSA to be underestimated when the incident wavelength is 337 nm.At 1060 nm,the assumption can cause the Cext,Cabs,and Csca to be underestimated,and lead the SSA to be overestimated.When the fractal dimension(Df)of chain-like soot inclusion increased from 1.8 to 2.6,the SSA of the particles with a Rwater of 0.20μm significantly decreased from 0.784 to 0.764 at 1060 nm.Moreover,the thickness of the water coating had a stronger effect on the particles with chain-like soot inclusion at 337 nm than that at 1060 nm.For the 337 nm wavelength,the difference between the Cext and Csca in Model B when Rwater=0.30 and 0.20μm was 0.588 and 0.587μm2,respectively.The differences were only 0.096 and 0.095μm2,respectively,for the 1060 nm wavelength.Based on the results calculated by the superposition T-matrix method,the ratios of P22(Θ)/P11(Θ)for chain-like soot with water coatings are not absolutely equal to 100%.When the Df value of aggregated soot inclusion is a constant,P22(Θ)/P11(Θ)decreased as the volume ratio of soot inclusion to the water droplet increased.Therefore,the ratio of P22(Θ)/P11(Θ)can be potentially used as an optical indicator to describe the morphology of non-spherical and/or inhomogeneous particles(or inclusion)for internal aerosol,fog,or cloud particles.Generally,although the thickness of the water coating,to a large extent,dominates the optical properties of the internal mixtures,the morphology of aggregated soot inclusion is a key factor for causing uncertainties in optical parameters.This is especially so when the volume ratio of the soot inclusion and water droplet is large,and the structure of the soot inclusion is loose. | Meng Fan Liangfu Chen Liangxiao Cheng Benben Xu Jinhua Tao Shenshen Li | 2019 | Particuology2019，17，6： | 0 |
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