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PurposeThis paper aims to describe a numerical procedure for approximating the potential distribution for a harmonic current point source, which is either buried in horizontally stratified multilayer earth, or positioned in the air. The procedure is very efficient and general. The total number of layers and the source position in relation to the medium model layers are completely arbitrary.Design/methodology/approachThe efficiency of the computation procedure is based on the successful application of the numerical approximation of two kernel functions of the integral expression for the potential distribution within an arbitrarily chosen layer of the medium model. Each kernel function of the observed layer is approximated using a linear combination of 15 real exponential functions. Using these approximations and the analytical integration based on the Weber integral, a simple expression for numerical approximation of potential distribution within boundaries of the observed medium layer is given. Potential retardation is taken into account approximately.FindingsThe numerical procedure developed for the approximation of potential distribution for a harmonic current point source, which is positioned arbitrarily in air or in horizontally stratified multilayer earth, is efficient, numerically stable and generally applicable.Research limitations/implicationsNumerical model developed for the harmonic current point source is the basis of a wider numerical models for computation of the harmonic and transient fields of earthing system, which consists of earthing grids buried in horizontally stratified multilayer earth and metallic structures in the air.Originality/valueThis is efficient and numerically stable frequency dependent harmonic current point source model. Potential retardation, which has been neglected at the first step of the approximation, is subsequently added to the potential expression in such a way that the Helmholtz differential equation has been approximately solved without introducing the Sommerfeld integrals.

Abstract-This paper presents a novel time-harmonic electromagnetic model for determining the current distribution on conductor grids in horizontally stratified multilayer medium. This model could be seen as a basis of the wider electromagnetic model for the frequency-domain transient analysis of conductor grids in multilayer medium. The total number of layers and the total number of conductors are completely arbitrary. The model is based on applying the finite element technique to an integral equation formulation. Each conductor is subdivided into segments with satisfying the thin-wire approximation. Complete electromagnetic coupling between segments is taken into account. The computation of Sommerfeld integrals is avoided through an effective approximation of the attenuation and phase shift effects. Computation procedure for the horizontally stratified multilayer medium is based on the successful application of numerical approximations of two kernel functions of the integral expression for the potential distribution within a single layer, which is caused by a point source of time-harmonic current. Extension from the point source to a segment of the earthing grid conductors is accomplished through integrating the potential contribution due to the line of time-harmonic current source along the segments axis.

This paper describes the algorithm for optimal distribution network reconfiguration using the combination of a heuristic approach and genetic algorithms. Although similar approaches have been developed so far, they usually had issues with poor convergence rate and long computational time, and were often applicable only to the small scale distribution networks. Unlike these approaches, the algorithm described in this paper brings a number of uniqueness and improvements that allow its application to the distribution networks of real size with a high degree of topology complexity. The optimal distribution network reconfiguration is formulated for the two different objective functions: minimization of total power/energy losses and minimization of network loading index. In doing so, the algorithm maintains the radial structure of the distribution network through the entire process and assures the fulfilment of various physical and operational network constraints. With a few minor modifications in the heuristic part of the algorithm, it can be adapted to the problem of determining the distribution network optimal structure in order to equalize the network voltage profile. The proposed algorithm was applied to a variety of standard distribution network test cases, and the results show the high quality and accuracy of the proposed approach, together with a remarkably short execution time.

This paper presents a numerical computation method for determining the magnetic field of high-current busducts of circular cross-section geometry, based on the subdivision of the busduct phase conductors and screens into the conductor filaments and the subsequent application of the mesh-current method, with the aid of the geometric mean distance method. The mathematical model takes into account the skin effect and the proximity effects, as well as the complete electromagnetic coupling between phase conductors and metal enclosures (i.e., screens) of the single-phase isolated busduct system (of circular cross-section geometry). This model could be readily applied to the computation of the magnetic field of the Gas Insulated Transmission Lines (GIL) as well.

This paper elaborates on several important outstanding issues in the state-of-art of overvoltage protection selection for modern wind farms. The lack of experience with this still-new technology, together with the inherent complexity of wind farm electrical systems, entails several unresolved issues pertinent to the topic of overvoltage protection, particularly in relation to lightning-initiated surges. Firstly, several aspects of the wind turbine lightning incidence, along with the issues related to the selection of lightning current parameters (pertinent to the wind farm overvoltage protection), are addressed in this paper. Secondly, several issues in the state-of-art models of the wind farm electrical systems-for the lightning surge analysis-are addressed and discussed. Here, a well-known ElectroMagnetic Transients Program (EMTP) software package is often employed, with all of its benefits and some limitations. Thirdly, the metal-oxide surge arrester energy capability and the issues related to the selection of the surge arrester rated energy-in relation to the direct lightning strikes to wind turbines-is addressed. Finally, some general considerations concerning the overvoltage protection selection for wind farm projects, particularly regarding the installation of the metal-oxide surge arresters, are provided as well.

Increased integration of renewable energy sources brings new challenges to the secure and stable power system operation. Operational challenges emanating from the reduced system inertia, in particular, will have important repercussions on the power system transient stability assessment (TSA). At the same time, a rise of the “big data” in the power system, from the development of wide area monitoring systems, introduces new paradigms for dealing with these challenges. Transient stability concerns are drawing attention of various stakeholders as they can be the leading causes of major outages. The aim of this paper is to address the power system TSA problem from the perspective of data mining and machine learning (ML). A novel 3.8 GB open dataset of time-domain phasor measurements signals is built from dynamic simulations of the IEEE New England 39-bus test case power system. A data processing pipeline is developed for features engineering and statistical post-processing. A complete ML model is proposed for the TSA analysis, built from a denoising stacked autoencoder and a voting ensemble classifier. Ensemble consist of pooling predictions from a support vector machine and a random forest. Results from the classifier application on the test case power system are reported and discussed. The ML application to the TSA problem is promising, since it is able to ingest huge amounts of data while retaining the ability to generalize and support real-time decisions.