Image Embedding of PMU Data for Deep Learning towards Transient Disturbance Classification

This paper presents a study on power grid disturbance classification by Deep Learning (DL). A real synchrophasor set composing of three different types of disturbance events from the Frequency Monitoring Network (FNET) is used. An image embedding technique called Gramian Angular Field is applied to transform each time series of event data to a two-dimensional image for learning. Two main DL algorithms, i.e. CNN (Convolutional Neural Network) and RNN (Recurrent Neural Network) are tested and compared with two widely used data mining tools, the Support Vector Machine and Decision Tree. The test results demonstrate the superiority of the both DL algorithms over other methods in the application of power system transient disturbance classification.Comment: An updated version of this manuscript has been accepted by the 2018 IEEE International Conference on Energy Internet (ICEI), Beijing, Chin

Production of antimatter 5,6^{5,6}Li nuclei in central Au+Au collisions at sNN=200\sqrt{s_{NN}} = 200 GeV

Combining the covariant coalescence model and a blast-wave-like analytical parametrization for (anti-)nucleon phase-space freezeout configuration, we explore light (anti-)nucleus production in central Au+Au collisions at $\sqrt{s_{NN}} = 200$ GeV. Using the nucleon freezeout configuration (denoted by FO1) determined from the measured spectra of protons (p), deutrons (d) and $^{3}$He, we find the predicted yield of $^{4}$He is significantly smaller than the experimental data. We show this disagreement can be removed by using a nucleon freezeout configuration (denoted by FO2) in which the nucleons are assumed to freeze out earlier than those in FO1 to effectively consider the effect of large binding energy value of $^{4}$He. Assuming the binding energy effect also exists for the production of $^5\text{Li}$, $^5\overline{\text{Li}}$, $^6\text{Li}$ and $^6\overline{\text{Li}}$ due to their similar binding energy values as $^{4}$He, we find the yields of these heavier (anti-)nuclei can be enhanced by a factor of about one order, implying that although the stable (anti-)$^6$Li nucleus is unlikely to be observed, the unstable (anti-)$^5$Li nucleus could be produced in observable abundance in Au+Au collisions at $\sqrt{s_{NN}} = 200$ GeV where it may be identified through the p-$^4\text{He}$ ($\overline{\text{p}}$-$^4\overline{\text{He}}$) invariant mass spectrum. The future experimental measurement on (anti-)$^5\text{Li}$ would be very useful to understand the production mechanism of heavier antimatter.Comment: 8 pages, 2 figures, 3 tables. Typos fixed and one ref added. Accepted version to appear in PL