Adjacent Graph Based Vulnerability Assessment for Electrical Networks Considering Fault Adjacent Relationships Among Branches

Security issues related to vulnerability assessment in electrical networks are necessary for operators to identify the critical branches. At present, using complex network theory to assess the structural vulnerability of the electrical network is a popular method. However, the complex network theory cannot be comprehensively applicable to the operational vulnerability assessment of the electrical network because the network operation is closely dependent on the physical rules not only on the topological structure. To overcome the problem, an adjacent graph (AG) considering the topological, physical, and operational features of the electrical network is constructed to replace the original network. Through the AG, a branch importance index that considers both the importance of a branch and the fault adjacent relationships among branches is constructed to evaluate the electrical network vulnerability. The IEEE 118-bus system and the French grid are employed to validate the effectiveness of the proposed method.National Natural Science Foundation of China under Grant U1734202National Key Research and Development Plan of China under Grant 2017YFB1200802-12National Natural Science Foundation of China under Grant 51877181National Natural Science Foundation of China under Grant 61703345Chinese Academy of Sciences, under Grant 2018-2019-0

Teleportation-Based Quantum Computation, Extended Temperley-Lieb Diagrammatical Approach and Yang--Baxter Equation

This paper focuses on the study of topological features in teleportation-based quantum computation as well as aims at presenting a detailed review on teleportaiton-based quantum computation (Gottesman and Chuang, Nature 402, 390, 1999). In the extended Temperley-Lieb diagrammatical approach, we clearly show that such topological features bring about the fault-tolerant construction of both universal quantum gates and four-partite entangled states more intuitive and simpler. Furthermore, we describe the Yang--Baxter gate by its extended Temperley-Lieb configuration, and then study teleportation-based quantum circuit models using the Yang--Baxter gate. Moreover, we discuss the relationship between the extended Temperley-Lieb diagrammatical approach and the Yang-Baxter gate approach. With these research results, we propose a worthwhile subject, the extended Temperley-Lieb diagrammatical approach, for physicists in quantum information and quantum computation.Comment: Latex, 47 pages, many figure

Gapless topological Fulde-Ferrell superfluidity induced by in-plane Zeeman field

Topological superfluids are recently discovered quantum matters that host topologically protected gapless edge states known as Majorana fermions - exotic quantum particles that act as their own anti-particles and obey non-Abelian statistics. Their realizations are believed to lie at the heart of future technologies such as fault-tolerant quantum computation. To date, the most efficient scheme to create topological superfluids and Majorana fermions is based on the Sau-Lutchyn-Tewari-Das Sarma model with a Rashba-type spin-orbit coupling on the }\textbf{\textit{x-y}}\textbf{ plane and a large out-of-plane (perpendicular) Zeeman field along the }\textbf{\textit{z}}\textbf{-direction. Here we propose an alternative setup, where the topological superfluid phase is driven by applying an in-plane Zeeman field. This scheme offers a number of new features, notably Cooper pairings at finite centre-of-mass momentum (i.e., Fulde-Ferrell pairing) and gapless excitations in the bulk. As a result, a novel gapless topological quantum matter with inhomogeneous pairing order parameter appears. It features unidirected Majorana surface states at boundaries, which propagate in the same direction and connect two Weyl nodes in the bulk. We demonstrate the emergence of such an exotic topological matter and the associated Majorana fermions in spin-orbit coupled atomic Fermi gases and determine its parameter space. The implementation of our scheme in semiconductor/superconductor heterostructures is briefly discussed.Comment: 8 pages, 5 figure

Leak localization in water distribution networks using a mixed model-based/data-driven approach

“The final publication is available at Springer via http://dx.doi.org/10.1016/j.conengprac.2016.07.006”This paper proposes a new method for leak localization in water distribution networks (WDNs). In a first stage, residuals are obtained by comparing pressure measurements with the estimations provided by a WDN model. In a second stage, a classifier is applied to the residuals with the aim of determining the leak location. The classifier is trained with data generated by simulation of the WDN under different leak scenarios and uncertainty conditions. The proposed method is tested both by using synthetic and experimental data with real WDNs of different sizes. The comparison with the current existing approaches shows a performance improvement.Peer ReviewedPostprint (author's final draft

pandapower - an Open Source Python Tool for Convenient Modeling, Analysis and Optimization of Electric Power Systems

pandapower is a Python based, BSD-licensed power system analysis tool aimed at automation of static and quasi-static analysis and optimization of balanced power systems. It provides power flow, optimal power flow, state estimation, topological graph searches and short circuit calculations according to IEC 60909. pandapower includes a Newton-Raphson power flow solver formerly based on PYPOWER, which has been accelerated with just-in-time compilation. Additional enhancements to the solver include the capability to model constant current loads, grids with multiple reference nodes and a connectivity check. The pandapower network model is based on electric elements, such as lines, two and three-winding transformers or ideal switches. All elements can be defined with nameplate parameters and are internally processed with equivalent circuit models, which have been validated against industry standard software tools. The tabular data structure used to define networks is based on the Python library pandas, which allows comfortable handling of input and output parameters. The implementation in Python makes pandapower easy to use and allows comfortable extension with third-party libraries. pandapower has been successfully applied in several grid studies as well as for educational purposes. A comprehensive, publicly available case-study demonstrates a possible application of pandapower in an automated time series calculation