Various methods have been proposed in the past for locating faults on distribution systems, which generally entail iterative procedures. This paper presents novel fault-location algorithms for ...overhead distribution systems that provide a unified solution that eliminates or reduces iterative procedures applicable to all types of faults. Two types of methods, respectively, for nonradial systems and radial systems have been proposed by utilizing voltage and current measurements at the local substation. The proposed methods are based on the bus impedance matrix, through which the substation voltage and current quantities can be expressed as a function of the fault location and fault resistance, a solution to which yields the fault location. The methods are developed in phase domain and, consequently, are naturally applicable to unbalanced systems. The assumptions made are that the distribution network parameters and topology are known so that the bus impedance matrix can be developed. Simulation studies have demonstrated that both types of methods are accurate and quite robust to load variations and measurement errors.
Diverse transmission line fault location algorithms have been proposed in the past depending on measurements available. Existing algorithms usually require measurements captured from buses of a ...faulted line. By taking advantage of the bus-impedance matrix technique, this paper presents a possible fault location approach for single-circuit lines utilizing only voltage measurements from one or two buses, which may be distant from the faulted line. With the addition of a fictitious bus where the fault occurs, the transfer impedances of this bus and other buses are revealed as a function of the fault location. Based on the relationship between the bus voltage change due to fault and the transfer impedance, the fault location can be derived. Shunt capacitance of the line is ignored first and then fully considered based on distributed parameter line model. Electromagnetic transients program simulation studies have shown quite encouraging results.
An extended Hubbard model on a honeycomb lattice with two orbitals per site at charge neutrality is investigated with unbiased large-scale quantum Monte Carlo simulations. The Fermi velocity of the ...Dirac fermions is renormalized as the cluster charge interaction increases, until a mass term emerges and a quantum phase transition from Dirac semimetal to valence bond solid (VBS) insulator is established. The quantum critical point is discovered to belong to the 3D N=4 Gross-Neveu chiral XY universality with the critical exponents obtained at high precision. Further enhancement of the interaction drives the system into two different VBS phases, the properties and transition between them are also revealed. Since the model is related to magic-angle twisted bilayer graphene, our results may have relevance towards the symmetry breaking order at the charge neutrality point of the material, and associate the wide range of universal strange metal behavior around it with quantum critical fluctuations.
Transmission line protective relaying algorithms usually require transmission line parameters as inputs and thus accuracy of line parameters plays a pivotal role in ensuring the reliable performance ...of relaying algorithms. Online estimation of line parameters is highly desirable and various methods have been proposed in the past. These methods perform well when the measurements utilized are accurate; they may yield erroneous results when the measurements contain considerable errors. Based on nonlinear optimal estimation theory, this paper puts forward an optimal estimator for deriving the positive sequence line parameters, capable of detecting and identifying the bad measurement data, minimizing the impacts of the measurement errors and thus significantly improving the estimation accuracy. The solution is based on the distributed parameter line model and thus fully considers the effects of shunt capacitances of the line. Case studies based on simulated data are presented for demonstrating the effectiveness of the new approach.
The paper deals with the estimation of a high dimensional covariance with a conditional sparsity structure and fast diverging eigenvalues. By assuming a sparse error covariance matrix in an ...approximate factor model, we allow for the presence of some cross-sectional correlation even after taking out common but unobservable factors. We introduce the principal orthogonal complement thresholding method 'POET' to explore such an approximate factor structure with sparsity. The POET-estimator includes the sample covariance matrix, the factor-based covariance matrix, the thresholding estimator and the adaptive thresholding estimator as specific examples. We provide mathematical insights when the factor analysis is approximately the same as the principal component analysis for high dimensional data. The rates of convergence of the sparse residual covariance matrix and the conditional sparse covariance matrix are studied under various norms. It is shown that the effect of estimating the unknown factors vanishes as the dimensionality increases. The uniform rates of convergence for the unobserved factors and their factor loadings are derived. The asymptotic results are also verified by extensive simulation studies. Finally, a real data application on portfolio allocation is presented.
Various transmission line fault location algorithms have been proposed in the past depending on the measurements available. These algorithms perform well when the measurements utilized are accurate; ...they may yield erroneous results when the measurements contain considerable errors. In some cases, there are redundant measurements available for fault location purposes, and it may be possible to design an optimal estimator for the fault location based on nonlinear estimation theories. This paper aims at proposing a possible method for deriving an optimal estimate of the fault location that is capable of detecting and identifying the bad measurement data, minimizing the impacts of the measurement errors and thus significantly improving the fault location accuracy. The solution is based on the distributed parameter line model and thus fully considers the effects of shut capacitances of the line. Since field data are not available, case studies based on simulated data are presented for demonstrating the effectiveness of the new method.
The variance-covariance matrix plays a central role in the inferential theories of high-dimensional factor models in finance and economics. Popular regularization methods of directly exploiting ...sparsity are not directly applicable to many financial problems. Classical methods of estimating the covariance matrices are based on the strict factor models, assuming independent idiosyncratic components. This assumption, however, is restrictive in practical applications. By assuming sparse error covariance matrix, we allow the presence of the cross-sectional correlation even after taking out common factors, and it enables us to combine the merits of both methods. We estimate the sparse covariance using the adaptive thresholding technique as in Cai and Liu J. Amer. Statist. Assoc. 106 (2011) 672-684, taking into account the fact that direct observations of the idiosyncratic components are unavailable. The impact of high dimensionality on the covariance matrix estimation based on the factor structure is then studied.
The practical application of membrane distillation (MD) for water purification is hindered by the absence of desirable membranes that can fulfill the special requirements of the MD process. Compared ...to the membranes fabricated by other methods, nanofiber membranes produced by electrospinning are of great interest due to their high porosity, low tortuosity, large surface pore size, and high surface hydrophobicity. However, the stable performance of the nanofiber membranes in the MD process is still unsatisfactory. Inspired by the unique structure of the lotus leaf, this study aimed to develop a strategy to construct superhydrophobic composite nanofiber membranes with robust superhydrophobicity and high porosity suitable for use in MD. The newly developed membrane consists of a superhydrophobic silica-PVDF composite selective skin formed on a polyvinylidene fluoride (PVDF) porous nanofiber scaffold via electrospinning. This fabrication method could be easily scaled up due to its simple preparation procedures. The effects of silica diameter and concentration on membrane contact angle, sliding angle, and MD performance were investigated thoroughly. For the first time, the direct contact membrane distillation (DCMD) tests demonstrate that the newly developed membranes are able to present stable high performance over 50 h of testing time, and the superhydrophobic selective layer exhibits excellent durability in ultrasonic treatment and a continuous DCMD test. It is believed that this novel design strategy has great potential for MD membrane fabrication.
This paper considers generalized least squares (GLS) estimation for linear panel data models. By estimating the large error covariance matrix consistently, the proposed feasible GLS estimator is more ...efficient than the ordinary least squares in the presence of heteroskedasticity, serial and cross-sectional correlations. The covariance matrix used for the feasible GLS is estimated via the banding and thresholding method. We establish the limiting distribution of the proposed estimator. A Monte Carlo study is considered. The proposed method is applied to an empirical application.
•A new fault location method for non-radial distribution systems is developed.•The method reduces iterative steps and is applicable to any type of faults.•The method is accurate, and insensitive to ...measurement errors and load variations.
Accurate location of faults in an electric power distribution system is important in maintaining system reliability. Diverse methods have been proposed in the past, which usually have different assumptions and thus are applicable to specific circumstances. This paper attempts to put forth a novel, general fault location method that is applicable to distribution networks with unbalances and multi-sources by employing voltages and currents at the local substation. The method considers feeder shunt capacitances and is applicable to both overhead and underground networks. The method does not require the fault type to be known, and is applicable to any type of faults. The method is based on bus impedance matrix that enables the establishment of the equations governing the relationship of the measurements and the fault location. Evaluation studies have demonstrated the effectiveness of the proposed method and its robustness with respect to potential measurement errors and load variations.
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