全球绿色航运走廊建设进展与中国应对之策

绿色航运走廊被视为航运业实现零排放的重要工具,逐渐成为国际航运领域的重要议题。分析全球绿色航运走廊建设现状与发展面临的问题以及由此给中国带来的机遇与挑战,结果表明全球绿色航运走廊倡议虽发展迅速,但仍存在内涵不清晰、建设标准未明确、燃料选择未统一、主体参与度不均、政策法规不完善等诸多问题,同时中国绿色航运走廊建设机遇与挑战并存。为此,提出中国建设绿色航运走廊的对策,包括加强理论研究、拉动消费需求、规划绿色航运走廊建设、建立绿色航运走廊人才体系、提供政策支持及建立绿色金融体系等。

基于光伏消纳能力模拟评估的配电网最优消纳方案规划选择

随着光能利用率的日益提升,配电网就地接入光伏愈发普遍,而大量分布式光伏并网则造成电压越限、消纳困难、经济效益低等诸多方面的问题。面对目前光伏优化配置的光伏接入总量,接入节点选择,节点容量配比的三大不确定难题,提出一套配电网光伏消纳能力模拟评估及消纳方案择优的方法。首先在分析配网线路结构角度的基础上定义节点全局电压影响度,据此衡量各节点接入光伏对全局电压的影响;然后基于蒙特卡洛法提出光伏消纳方案随机模拟与消纳能力近似评估的方法,并通过基于节点全局电压影响度设计的光伏接入节点位置抽样方法来提高模拟评估的效率和精度;最后综合考虑各候选最优消纳方案的近似最大消纳容量、年运行电压越上限指标及年均投资效益,采用逼近理想解排序法(technique for order preference by similarity to an ideal solution,TOPSIS)选出经济性和安全性最优的方案。基于IEEE33节点系统算例分析,有效验证了所述方法的适用性。

A method of searching for supernova candidates from massive galaxy spectra

This paper presents a novel spectroscopic method for searching for supernova candidates from massive galaxy spectra,which is expected to be applied to the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST).This method includes mainly five steps.The first step is spectral preprocessing,including removing spectral noise using wavelet transform,spectral de-redshift,etc.The second step is decomposition of galactic spectra;we can get the galaxy component and supernova component and calculate the Supernova Statistical Characterization Vector (SNSCV) of each galaxy spectrum.The third step is to decrease samples in all the galaxy spectral datasets according to SNSCV of each spectrum,and to use the LOF (Local Outlier Factor)-based outlier detection algorithm to obtain the preliminary selected spectral data.The fourth step is template matching by cross-correlation,according to the matched results we get the secondary selected spectral data.Finally,we choose the final supernova candidates manually through checking the spectral features characteristic of a supernova.By the spectroscopic method proposed in this paper,thirty-six supernova candidates have been detected in a dataset including 294843 galaxy spectra from the Sloan Digital Sky Survey Data Release 7.Nine of these objects are detected first and the other twenty-seven have been reported in other publications (fifteen of which are detected and reported first by us).The twenty-four new super-nova candidates include twenty Ia type supernova candidates,three Ic type supernova candidates and one II type supernova candidate.

Search for carbon stars and DZ white dwarfs in SDSS spectra survey through machine learning

Carbon stars and DZ white dwarfs are two types of rare objects in the Galaxy. In this paper, we have applied the label propagation algorithm to search for these two types of stars from Data Release Eight （DR8） of the Sloan Digital Sky Survey （SDSS）, which is verified to be efficient by calculating precision and recall. From nearly two million spectra including stars, galaxies and QSOs, we have found 260 new carbon stars in which 96 stars have been identified as dwarfs and 7 identified as giants, and 11 composition spectrum systems （each of them consists of a white dwarf and a carbon star）. Similarly, using the label propagation method, we have obtained 29 new DZ white dwarfs from SDSS DR8. Compared with PCA reconstructed spectra, the 29 findings are typical DZ white dwarfs. We have also investigated their proper motions by comparing them with proper motion distribution of 9,374 white dwarfs, and fotmd that they satisfy the current observed white dwarfs by SDSS generally have large proper motions. In addition, we have estimated their effective temperatures by fitting the polynomial relationship between effective temperature and g-r color of known DZ white dwarfs, and found 12 of the 29 new DZ white dwarfs are cool, in which nine are between 6,000 K and 6,600 K, and three are below 6,000 K.