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| 1 | Concentration and source identification of polycyclic aromatic hydrocarbons and phthalic acid esters in the surface water of the Yangtze River Delta,China显示文摘The pollution from polycyclic aromatic hydrocarbons(PAHs) and phthalic acid esters(PAEs) in the surface water of the rapidly urbanized Yangtze River Delta region was investigated.Fourteen surface water samples were collected in June 2010.Water samples were liquid-liquid extracted using methylene chloride and analyzed by gas chromatography-mass spectrometry.Concentrations of PAHs and PAEs ranged 12.9-638.1 ng/L and 61-28550 ng/L,respectively.Fluoranthene,naphthalene,pyrene,phenanthrene,di-2ethylhexyl phthalate,and di-n-butyl phthalate were the most abundant compounds in the samples.The water samples were moderately polluted with benzo[a]pyrene according to China's environmental quality standard for surface water.The two highest concentrations of PAHs and PAEs occurred in samples from Taihu Lake,Wuxi City and the western section of Yangchenghu Lake.Potential sources of pollution at S7 were petroleum combustion and the plastics industry,and at Yangchenghu Lake were petroleum combustion and domestic waste.Pollution in samples from the Beijing-Hangzhou Grand Canal originated from diesel engines.There were no obvious sources of pollution for the other water samples.These results can be used as reference levels for future monitoring programs of pollution from PAHs and PAEs. | Lifei Zhang Liang Dong Lijun Ren Shuangxin Shi Li Zhou Ting Zhang Yeru Huang | 2012 | Journal of Environmental Sciences2012，24，2： | 56 |
| 2 | Neural Network Predictive Control of Variable-pitch Wind Turbines Based on Small-world Optimization Algorithm显示文摘通过将混沌映射用于产生初始节点集和进行算子构造,提出一种新的基于实数编码的混沌小世界优化算法。采用4种算法对多例复杂函数的优化问题进行仿真试验,表明所提算法具有能够有效避免陷入局部极小值、快速搜索到最优值的能力。将上述方法应用于变桨距风电机组启动并网时的转速控制,提出一种基于混沌小世界优化算法的神经网络预测控制策略,其预测模型由基于现场数据的神经网络模型建立。仿真与实际测试结果表明,该系统可以根据风速扰动提前预测电机的转速变化,使控制器超前动作,保证系统输出跟踪参考轨迹的方向稳步改变,确保风电机组平稳并网。 | WANG Shuangxin LI Zhaoxia LIU Hairui | 2012 | 中国电机工程学报2012，32，30： | 8 |
| 3 | Small-world Neural Network and Its Performance for Wind Power Forecasting显示文摘A small-world neural network has stronger generalization ability with high transfer efficiency than that of the regular neural networks.This paper presents two novel smallworld neural networks,the Watts-Strogatz small-world based on a BP neural network(WSBP)and a Newman-Watts smallworld neural network based on a BP neural network(NWBP),related to previous research of complex networks.The algorithms are developed separately by adopting WS and NW small-world networks as their topological structures,and their derivation and convergence criterion are progressively discussed.After that,the proposed models are subsequently tested by two typical nonlinear functions which confirm their significant improvement over the regular BP networks and other algorithms.Finally,a wind power prediction system is advanced to verify their generalization abilities,and show that the models are practically feasible and effective with improved accuracy and acceptable forecasting errors caused by wind fluctuation and randomness with a time scale up to 24 h. | Shuangxin Wang Xin Zhao Hong Wang Meng Li | 2020 | CSEE Journal of Power and Energy Systems2020，6，2： | 2 |
| 4 | Organochlorine pesticides contamination in surface soils from two pesticide factories in Southeast China显示文摘 | Zhang Lifei Dong Liang Shi Shuangxin | 2009 | Chemosphere2009，77，： | 1 |
| 5 | Weakly Singular Symmetric Galerkin Boundary Element Method for Fracture Analysis of Three-Dimensional Structures Considering Rotational Inertia and Gravitational Forces显示文摘The Symmetric Galerkin Boundary Element Method is advantageous for the linear elastic fracture and crackgrowth analysis of solid structures,because only boundary and crack-surface elements are needed.However,for engineering structures subjected to body forces such as rotational inertia and gravitational loads,additional domain integral terms in the Galerkin boundary integral equation will necessitate meshing of the interior of the domain.In this study,weakly-singular SGBEM for fracture analysis of three-dimensional structures considering rotational inertia and gravitational forces are developed.By using divergence theorem or alternatively the radial integration method,the domain integral terms caused by body forces are transformed into boundary integrals.And due to the weak singularity of the formulated boundary integral equations,a simple Gauss-Legendre quadrature with a few integral points is sufficient for numerically evaluating the SGBEM equations.Some numerical examples are presented to verify this approach and results are compared with benchmark solutions. | Shuangxin He Chaoyang Wang Xuan Zhou Leiting Dong Satya N.Atluri | 2022 | Computer Modeling in Engineering & Sciences2022，，6： | 1 |
| 6 | Review of evaluation criteria and main methods of wind power forecasting显示文摘 | Zhao Xin Wang Shuangxin Li Tao | 2011 | Energy Procedia2011，12，： | 1 |
| 7 | Concentrations and possible sources of polychlorinated biphenyls in the surface water of the Yangtze River Delta, China显示文摘 | Lifei Zhang Shuangxin Shi Liang Dong Ting Zhang Li Zhou Yeru Huang | 2011 | Chemosphere2011，，3： | 1 |
| 8 | Organochlorine pesticides contamination in surface soils from two pesticide factories in Southeast China显示文摘 | Lifei Zhang Liang Dong Shuangxin Shi Li Zhou Ting Zhang Yeru Huang | 2009 | Chemosphere2009，，5： | 1 |
| 9 | Passive air sampling of organochlorine pesticides and polychlorinated biphenyls in the Yangtze River Delta, China: Concentrations, distributions, and cancer risk assessment显示文摘 | Lifei Zhang Liang Dong Wenlong Yang Li Zhou Shuangxin Shi Xiulan Zhang Shan Niu Lingling Li Zhongxiang Wu Yeru Huang | 2013 | Environmental Pollution2013，，： | 1 |
| 10 | Convergence analysis of the Tabu real-coded small-world optimization algorithm 显示文摘 | ZHAO Xin WANG Shuangxin | 2014 | Engineering Optimization2014，46，4： | 1 |
| 11 | Composite Model-free Adaptive Predictive Control for Wind Power Generation Based on Full Wind Speed显示文摘Aiming at the problem that the existing model-based control strategy cannot fully reflect stochastic fluctuations of wind power,this paper presents a model-free adaptive predictive controller(MFAPC)for variable pitch systems with speed disturbance suppression.First,an improved small-world neural network with topology optimization is used for 15-second-ahead forecasting of wind speed,whose rolling time is 1s,and the predicted value serves as a feedforward to obtain the early compensation variation of the pitch angle.Second,a function of the multi-objective optimization at full wind speed with optimal power point tracking and minimum control variation is constructed,and an advanced one-step adaptive predictive control algorithm for wind power is proposed based on the online estimation and prediction of the time-varying pseudo partial derivative(PPD).In addition,the compound MFAPC framework is synthetically obtained,whose closed-loop effectiveness is verified by a BP-built pitch system based on the SCADA data with all working conditions.Robustness of the schemes has been analyzed in terms of parametric uncertainties and different operating conditions,and a detailed comparison is finally presented.The results show that the proposed MFAPC can not only effectively suppress the random disturbance of wind speed,but also meet the stability of wind power and the security of grid-connections for all operating conditions. | Shuangxin Wang Jianshen Li Zhongsheng Hou Qingye Meng Meng Li | 2022 | CSEE Journal of Power and Energy Systems2022，8，6： | 0 |
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