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• Formulation of integrated model considering non-homogeneous medium and non-linearities. • Computational implementation based on two-dimensional Transmission Line Modeling method. • Study on the behavior of high frequency electromagnetic waves. • Impact that ionization effect causes to voltage reduction. This work presents a two-dimensional Transmission Line Modeling (TLM-2D) method for modeling non-homogeneous media and non-linearities. The presented method is derived on top of the classical TLM-2D method with reactive and conductive stubs to modify the properties of the medium. Taking advantage of the analogy between electromagnetic and circuits theories, nonlinearities such as soil ionization, can be solved numerically through models formulated to represent electrical conductors, such as grounding systems. Using this analogy, the analysis can be extended more generically to non-homogenous and lossy media. Then, nonlinearity phenomena is included in the classical TLM-2D model through the dynamic variation of circuit parameters. This variation is obtained through the developed analytical based tests. Computational implementation details are also reported. A case study is presented considering a grounding grid mesh in non-homogeneous media submitted to lightning surges. Comparative test results with the state of the art highlight the improved precision of the presented solution. [ABSTRACT FROM AUTHOR]

This paper presents further contributions to smart grids cyber-physical security as a malicious data attack. The contributions are twofold. First, a formal proof of how parameter errors spread out on the measurement function having a parameter with error. The largest composed measurement error property, in its normalized form, is then demonstrated for this case of error. Second, a methodology for smart grid cyber-physical malicious data injection correction is presented. Current state of the art solutions corrects simultaneous attacks assuming measurements or parameters without error. However, how may one correct a measurement if the parameter might be simultaneously in error or the other way around? In this paper, a relaxed model strategy for such is presented. Attacks are processed simultaneously and analyzed using only the framework of measurement gross error analysis. Cyber-attack detection is made through a Chi-square ( χ 2 ) Hypothesis Testing ( HT ) applied to the normalized composed measurement error ( CME N ). Composed errors are estimated with measurements’ innovation index ( II ). Cyber-attack identification is made through the largest normalized error test property. Cyber-attack correction is made considering cyber-attack type and using the composed normalized error ( CNE ) in a relaxed model strategy. The proposed solution works for malicious measurement and parameter data attacks. Still, the state estimation software does not need major changes. Validation is made on the IEEE 14-bus and 57-bus systems. [ABSTRACT FROM AUTHOR]

This work presents an analytical methodology for synchronous generators stator faults protection. The proposed method is built on a differential protection relay strategy. A morphological filter is applied on the differential current providing real-time signal characterization. Unlike the traditional percentage differential relay, the proposed analytical methodology is able to detect all types of stator faults, including those close to the neutral end, which generates small differential currents due to the high impedance grounding of generator. Validation is done with OPAL-RT using a phase-domain synchronous machine model, which represents realistic operating conditions. The results of test cases highlights the method's dependability and security. Easy to implement models without hard-to-design parameters indicates the method’s potential for real-life applications. [ABSTRACT FROM AUTHOR]

This paper presents an analytical methodology for smart grids cyber-physical security based on gross error analysis. The presented methodology is built on the Weighted Least Square (WLS) state estimator (SE) formulation. Although cyber-physical security is a wide subject, in this paper Cyber-Attacks are modeled as bad data. Detection, identification and correction of multiple and simultaneous cyber-attacks on power grid's SCADA system, or network database, are investigated. Cyber-attack detection is made through a Chi-square ( χ 2 ) Hypothesis Testing (HT) applied to the composed measurement error ( CME ). Composed errors are estimated with measurements’ innovation index ( II ). Cyber-attack identification is made through the Largest Normalized Error Test property. Cyber-attack correction is made considering cyber-attack type and using the composed normalized error ( CNE ). One important advantage of the presented method is it does not require a previous knowledge of how the attack was performed, as far as it is restricted to a change of measurements, parameters or topology, since the error is estimated and then the bad data is corrected. A significant advantage of this correction is that it avoids potential local or global unobservable conditions, since it does not delete any measurement of the measurement set. Validation of the proposed methodology is made on the IEEE 14-bus and 57-bus systems. Simulations show the reliability and robustness of the proposed methodology even when the cyber-attack occurs simultaneously on SCADA data and network database. [ABSTRACT FROM AUTHOR]

High impedance fault location still represents a challenge for protection engineers. In this work, an analytical formulation for high impedance fault location in power distribution systems is presented, based on system parameters estimation. The proposed method is based on a frequency domain system model, developed considering a high impedance fault model composed by two antiparallel diodes and an arc resistance. The proposed model is an overdetermined nonlinear algebraic system of equations in which the solution is obtained through a Weighted Least Square approach. A residual analysis is applied for estimate selection. The proposed method considers the capacitive effect through an exact line segment model for overhead distribution lines, using only local voltages and currents as input data. Validation is done through numerical simulations using the IEEE system 13 buses test feeder, a real distribution system from the RGE Sul Power Utility (Southern Brazil), and a real high impedance fault recorded from a digital relay. Comparative test results with the state-of-the-art highlights the method's high accuracy, indicating potential aspects for real life application. Overall average errors of 0.3% considering a complete HIF model were obtained, and a 1.39% error considering a real HIF in a rural feeder. The formulation is currently used by protection engineers at RGE Sul as a reliability oriented tool. [ABSTRACT FROM AUTHOR]

Loss‐of‐excitation (LOE) relays work under pre‐defined operating characteristics. If an abnormal condition should arise, such operating characteristics might not be suitable for current system conditions. In this study, an adaptive real‐time data‐based analytical methodology is proposed for improving LOE protection performance. The core idea is to generate in real time an adaptive operating characteristic for the Mho relay, based on the well know Berdy's method. The adaptive Mho operating characteristic is derived through the proposed methodology using the generator capability curve. Validation is obtained through comparative simulation test cases using DigSilent Power Factory® program. Test case results show that the proposed protection adaptive analytical methodology displays secure and effective high speed LOE detection, indicating potential for real‐life applications. [ABSTRACT FROM AUTHOR]

In this paper a two steps approach for the power system state estimation is proposed. The first step is the gross error detection test when all the measurements are assumed as possible of having errors. With that assumption, a rule for the measurement’s weights as being the inverse of a constant percentage of the measurement’s magnitudes is proposed. Then, using the error as the objective function of the state estimation (SE) process to be minimized, the gross error analysis is performed. In case a gross error is detected, the Composed Measurement Error, in its normalized form ( CME N ), is used to identify the measurement(s) with error(s). The measurement(s) with error(s) is corrected using the Composed Normalized Error ( CNE ). In the second step, the state estimation is again performed, but using as the weight for each measurement the inverse of the measurement’s standard deviation as proposed in the classical estimators. In this step, the set of measures is the original set, but with the measures flagged with gross errors replaced by their estimated values. The IEEE-14, IEEE-57 bus systems and the 45-bus equivalent of the Southern part of Brazil are used to perform the tests. [ABSTRACT FROM AUTHOR]

Highlights: [•] The work presents a contribution to the study of human safety against lightning. [•] We investigate the influence of soils properties associated to a grounding system. [•] The study considers a representative human body composed by electric circuits. [•] The step, contact and transferred potentials mechanism are investigated. [•] The current and the generated energy passing through the heart are evaluated. [ABSTRACT FROM AUTHOR]

This paper presents an extended methodology based on the transmission line modeling method (TLM) aiming at a soil ionization representation for the simulation of grounding systems. This natural phenomenon can be represented by considering the variation of the conductive components present in the TLM circuit. The proposed analytical formulation is introduced with a focus on the computational implementation of the TLM method in one dimension. The method is not subject to divergent solutions, being numerically stable and the methodology can be incorporated into a general algorithm irrespective of the soil properties or characteristics of the grounding electrode and lightning surge. [ABSTRACT FROM AUTHOR]

State-of-the art physics-model based dynamic state estimation generally relies on the assumption that the system's transition matrix is always correct, the one that relates the states in two different time instants, which might not hold always on real-life applications. Further, while making such assumptions, state-of-the-art dynamic state estimation models become unable to discriminate among different types of anomalies, as measurement gross errors and sudden load changes, and thus automatically leads the state estimator framework to inaccuracy. Towards the solution of this important challenge, in this work, a hybrid adaptive dynamic state estimator framework is presented. Based on the Kalman Filter formulation, measurement innovation analytical-based tests are presented and integrated into the state estimator framework. Gross measurement errors and sudden load changes are automatically detected, identified, and corrected, providing continuous updating of the state estimator. Towards such, the asymmetry index applied to the measurement innovation is introduced, as an anomaly discrimination method, which assesses the physics-model-based dynamic state estimation process in different piece-wise stationary levels. Comparative tests with the state-of-the-art are presented, considering the IEEE 14, IEEE 30, and IEEE 118 test systems. Easy-to-implement-model, without hard-to-design parameters, build-on the classical Kalman Filter solution, highlights potential aspects towards real-life applications. [ABSTRACT FROM AUTHOR]

Power system restoration (PSR) has been a subject of study for many years. In recent years, many techniques were proposed to solve the limitations of the predetermined restoration guidelines and procedures used by a majority of system operators to restore a system following the occurrence of a wide area disturbance. This paper discusses limitations encountered in some currently used PSR techniques and a proposed improvement based on artificial neural networks (ANNs). The proposed scheme is tested on a 162-bus transmission system and compared with a breadthsearch restoration scheme. The results indicate that the use of ANN in power system restoration is a feasible option that should be considered for real-time applications. [ABSTRACT FROM AUTHOR]

The high penetration of renewable sources of energy in electrical power systems implies an increase in the uncertainty variables of the economic dispatch (ED). Uncertainty costs are a metric to quantify the variability introduced from renewable energy generation, that is to say: wind energy generation (WEG), run-of-the-river hydro generators (RHG), and solar photovoltaic generation (PVG). On other side, there are associated uncertainties to the charge/uncharge of plug-in electric vehicles (PEV). Thus, in this paper, the uncertainty cost functions (UCF) and their marginal expressions as a way of modeling and assessment of stochasticity in power systems with high penetration of smart grids elements is presented. In this work, a mathematical analysis is presented using the first and second derivatives of the UCF, where the marginal uncertainty cost functions (MUCF) and the UCF's minimums for PVG, WEG, PEV, and RHG are derived. Further, a model validation is presented, considering comparative test results from the state of the art of the UCF minimum, developed in a previous study, to the minimum reached with the presented (MUCF) solution. [ABSTRACT FROM AUTHOR]

• Unbalanced parameter correction model against false data injection attacks. • Cyber-physical security framework for bad data analysis of FDI attacks. • Real-time multiple simultaneous measurement and parameter false data injection processing. This paper presents a correction model for malicious, unbalanced parameter false data injection cyber-attacks. Current state-of-art solutions can detect, identify and correct balanced parameter false data injection cyber-attacks. Thus, they consider all the parameters as equal in error, which means the methods will only work when the same percentage attack happens to each parameter. In this paper, a new correction model using a parameter correction Jacobian matrix, τ , and a Taylor series approximation is presented. A framework for measurement gross error analysis is deployed in processing and analyzing cyber-attacks. Chi-square χ 2 Hypothesis Testing applied to the normalized composed measurement error (CMEN) is considered for cyber-attacks detection, while the largest CMEN error test is used for identification. Validation is performed on the IEEE 14-bus and 118-bus systems. Easy-to-implement model, without hard-to-design parameters, built on the classical weighted least squares solution, highlights potential aspects for real-life implementation. [ABSTRACT FROM AUTHOR]

• Identification of vulnerable NTL system areas based on concepts of measurement's innovation and n-tuple of critical measurements. • Synthetic measurement model for GE analysis enhancement. • Framework for NTL estimation in unbalanced distribution networks. This paper presents a hybrid data-driven physics model-based framework for distribution networks nontechnical power loss estimation. Nontechnical power loss is defined as energy delivered to the consumers but not billed by the utility. These losses, unlike technical losses, are not inherent to the process of transportation of electricity. State-of-the-art solutions for nontechnical power loss estimation are either data-driven or physics model-based. However, due to the evolving nature of nontechnical power losses, data-driven solutions by themselves are not sufficient. Physics model-based analytical solutions, otherwise, which consider a quasi-static system model, rely solely on physics phenomena observation, however it is virtually impossible to model all grid dynamics. In this case, the nexus of data-driven physics model-based analytic models enable the solution of the problem. The hybrid framework is composed of three interdependent processes. First, an unbalanced load flow analysis is performed to obtain an initial estimate of the operating system state. Second, a data-driven method for consumer classification is applied. Third, synthetic measurements are created considering the measurement's innovation and n -tuple of critical measurements aiming to improve gross error analysis. Solution validation is made considering the IEEE 4-bus, 13-bus and 123-bus unbalance test feeders. Comparative test results highlight decreased nontechnical power loss estimation errors. Simplicity of implementation, with easy-to-obtain parameters, built on the classical weighted least squares state estimator, indicate potential aspects for real-life applications. [ABSTRACT FROM AUTHOR]

Contingency Constrained Optimal Power Flow (CCOPF) differs from traditional Optimal Power Flow (OPF) because its generation dispatch is planned to work with state variables between constraint limits, considering a specific contingency. When it is not desired to have changes in the power dispatch after the contingency occurs, the CCOPF is studied with a preventive perspective, whereas when the contingency occurs and the power dispatch needs to change to operate the system between limits in the post-contingency state, the problem is studied with a corrective perspective. As current power system software tools mainly focus on the traditional OPF problem, having the means to solve CCOPF will benefit power systems planning and operation. This paper presents a Quadratically Constrained Quadratic Programming (QCQP) formulation built within the matpower environment as a solution strategy to the preventive CCOPF. Moreover, an extended OPF model that forces the network to meet all constraints under contingency is proposed as a strategy to find the power dispatch solution for the corrective CCOPF. Validation is made on the IEEE 14-bus test system including photovoltaic generation in one simulation case. It was found that in the QCQP formulation, the power dispatch calculated barely differs in both pre- and post-contingency scenarios while in the OPF extended power network, node voltage values in both pre- and post-contingency scenarios are equal in spite of having different power dispatch for each scenario. This suggests that both the QCQP and the extended OPF formulations proposed, could be implemented in power system software tools in order to solve CCOPF problems from a preventive or corrective perspective. [ABSTRACT FROM AUTHOR]

• A 2D Densenet does not need prior extraction of features for PQD signals by some mathematical method, which eliminates the 2-step based model and reduces computational burden. • Spatio-temporal environment characteristics are considered in a data driven based framework. A 2D Densenet solution allows for the reduction in the quantity of filters per convolutional layer of Densenet used to classify PQDs. • Due the densely connected layers, the 2D Densenet size is smaller leading it to a faster classification time. The fast and accurate diagnosis of power quality disturbances (PQD) aids in avoiding shutdowns and unnecessary procedures, concerning electric energy distribution systems. As such, a number of techniques have been tested and applied in order to reach this objective. Majority of the techniques applied are two-step based. On the first step, power quality disturbances features are extracted. Second step, considering features extracted, disturbance classification is implemented. Recently, relevant literature has presented data-driven signal processing-based approaches, as deep convolutional neural networks (DCNN), which can implement both processing steps while providing automated recognition of patterns and outliers in data. However, not considered by state-of-art, power quality disturbances are evolving in nature, while all possible regularities might not be represented in the dataset. In this work a 2 Dimension Densely Connected Convolutional Network (2D-DenseNet) framework is presented. Case study with synthetic disturbance events are analyzed. Easy-to-implement formulation, built on the 2D-DenseNet, without hard-to-design parameters, highlight potential aspects for real-life implementation. [ABSTRACT FROM AUTHOR]

In this paper a geometrical approach is described to detect, identify, and recover multiple gross errors in power system state estimation. Using the classical WLS estimator, the measurement residuals is computed, and then the error is composed. For the detection and identification of the measurements with gross errors, the composed measurement error in the normalized form (CME^N) is used. The measurement magnitude corrections otherwise are performed using the composed normalized measurement error (CNE). To give support to the detection and identification of the measurements containing gross errors, a generalization of the classical largest normalized residual test is provided. [ABSTRACT FROM PUBLISHER]

• Comprehensive physics-based analytical model for HIF location. • Statistical behavior of estimates is analyzed to identify the faulted section. • One-ended data based frequency domain measurement model. This paper presents a physics-based analytical model for high impedance fault location in power distribution systems. The presented analytical solution is composed by two interdependent processes. First, fault distance is estimated through a Weighted Least Square approach applied to solve an overdetermined and nonlinear algebraic system of equations. Second, an analytical method based on the statistical behavior of the estimates obtained from the frequency domain system model solution is presented to address the multiple estimates problem, identifying the faulted section. The presented fault location physics-based analytical model considers the capacitive effect of distribution lines. Furthermore, voltages and currents measured from only one terminal are used. The formulation is evaluated using the IEEE 13-bus and a modified version of the IEEE 34-bus test feeders. Comparative analysis with state-of-the-art methods is presented. Average errors of 1.95% are obtained. Easy to implement analytical model, without hard to derive parameters, built on the weighted least squares state estimator, highlight potential aspects for real-life applications. [ABSTRACT FROM AUTHOR]

• Explicit mathematical model of interdependency between PMU cost and error analysis. • Formulation of a weighted goal programming framework applied to the OPP problem. • WGP allows for customization based on the user's needs and additional goals. • Improved topological observability constraint which considers all PMU measurements. This paper proposes a multi-objective mixed-integer linear programming (MILP) model for the optimal phasor measurement unit (PMU) placement (OPP) problem. A majority of the solutions presented for the OPP problem focus on minimizing cost while guaranteeing system observability. While this is a good approach to the OPP problem, the effect of PMU allocation on various energy management system applications should also be considered. This paper addresses the OPP problem considering PMU installation costs, system observability, and gross error detection. In order to allocate PMUs considering gross error detection, the Vulnerability Index (VI) is used to quantify the vulnerability of each element in the system. A weighted goal programming (WGP) framework, which allows for the optimization of contradictory goals, which is a characteristic of the goals considered in this paper, is presented. The goals and weights of the framework are user inputs to the program besides a hard budget restriction. The results of this paper show how the WGP framework allows the priorities of the decision maker to influence the final PMU allocation presented by the MILP, making this model a valuable framework for utilities planning to install PMUs on their network. [ABSTRACT FROM AUTHOR]

This article presents a methodology to calculate grounding potentials in adjacent electrodes present in high-voltage substations subjected to a short-circuit current dissipated in the main grid. The contribution of the technique is the consideration of the coupling by the soil among electrodes taking into account a two-layer soil and irregular geometry of the conductors. This problem is of special concern due to the presence of passers-by near metallic fences, not directly connected to the grounding grid, whose potentials usually have not been evaluated. In this context, the article presents a general analytical formulation aiming to estimate the potential in multiple electrodes, leading to a possible risk to human beings close to the substation. Sensitivity studies are performed in order to evaluate the effect of the soil resistivity and the distance from the faulted grid and the coupled electrode. A practical application in a substation grounding system is discussed. Finally, a huge grounding system is evaluated in order to verify the robustness of the proposed formulation. [ABSTRACT FROM AUTHOR]

Considering urban substations ground grid diagnosis, some real-physical constraints result in measurement process challenges: 1) limited length between electrodes used to measure the equivalent impedance of the grounding system; 2) to determine the current that flows from ground grid conductors to the earth; and 3) to determine the grid resistance. In this scenario, an adequate diagnosis of the safety offered by the ground grid under test when a ground fault occurs is not a trivial task. This article describes a methodology that allows a reliable diagnosis regarding the safety provided by a substation ground grid. The methodology is applied to the parameters obtained in performed field tests. The method has two steps. First, the fall-of-potential method with reduced distances between electrodes is used to determine the equivalent impedance of the grounding system. Then, the ground current is obtained. In both stages, optimization techniques are applied to the specific equations that govern the phenomenon under investigation. Comparative case studies considering real-life data illustrate the effectiveness of the method. [ABSTRACT FROM AUTHOR]

Highlights • The modified Distributed Gradient Projection algorithm with a constant step size can handle non-strictly and convex consumer costs. • We establish a bound on the step size such that the algorithm behaves in a stable manner. • Numerical tests with the IEEE 39-bus system show that predictions are still accurate even when consumer costs are non-convex. • The algorithm is robust to model mismatch and time delays. • Its performance suffers if the dynamic response of the loads is slow. Abstract The Distributed Gradient Projection (DGP) algorithm was proposed in prior work to allow loads to provide contingency service to the grid using local noisy frequency measurements by varying their demand. Convergence of DGP was established in prior work for a decaying step size. In this paper we modify the algorithm to using a constant step size—constant step size being much more useful for practical implementation. We provide a convergence analysis of the modified algorithm, which we call DGP-C (DGP with Constant step size) and perform extensive simulations in the IEEE 39-bus test system. These studies (i) demonstrate that the DGP-C algorithm is robust to several assumptions made in the analysis and (ii) reveal which factors among the many tested (measurement noise, loads' response time, etc.) have significant effect on the algorithm's performance. [ABSTRACT FROM AUTHOR]

This paper presents a hybrid method based on the transmission line modeling method (TLM) aiming to represent the soil ionization effect for grounding systems simulation. This natural phenomenon can be better represented by taking into account the variation of the conductive components present in the TLM circuit and considering the residual resistivity remaining in the soil. The proposed analytical formulation is developed with a focus on the computational implementation of the method. The model is validated by comparing synthetized test results with measured data and other numerical models (residual resistivity, TLM, and analytical model). High precision together with an easy to implement formulation indicates that the methodology presents potential for real-life applications. [ABSTRACT FROM AUTHOR]

In this paper a frequency domain formulation for nonlinear arcing fault location is presented. The proposed fault location formulation uses as input data first cycles after the fault inception voltages and currents. The formulation is based on circuit analysis and a parameter estimation method. To consider the main characteristics of nonlinear arcing faults, a time varying resistance embedded in a nonlinear model is proposed and used. The formulation is developed for the case of the most frequent single line-to-ground faults using phase components. The effects of fault inception angle, time-varying series resistance, source impedance, load flow, sampling frequency and others factors are investigated and analyzed. This new approach was successfully tested through computer simulation and real data obtained from a Southern Brazilian Energy Utility. The proposed method was developed as dedicated software and is currently used by CEEE-GT. [ABSTRACT FROM AUTHOR]

This paper presents the development of an analytical formulation for estimating the potential on the soil surface, caused by electric current calculated on a grounding conductor. The formulation has a great significance in its use in conjunction with 1-D numerical methods, which are not able to determine such potentials directly. The proposed study focuses on lightning surges considering the frequency dependence of the soil properties. First, the subject is introduced emphasizing important aspects related to the analysis and representation of grounding systems against lightning. Afterward, the proposed analytical formulation is introduced with a focus on the computational implementation of the transmission line modeling method in 1-D. Simulations were carried out considering a typical horizontal electrode used as grounding in the power electric system. The formulation was validated by comparing the results with the solution based on the electromagnetic model (CDEGS Software), which is considered the most stringent for the solution of full Maxwell equations due to their minimum approaches. The results demonstrate that the generalized formulation presents good accuracy, contributing to an improved representation of grounding systems based on numerical techniques in 1-D. [ABSTRACT FROM AUTHOR]

• A Multi-agent System (MAS) is suggested for distribution systems fault section estimation;. • The authors discussed the use of smart meters in a smart grid environment;. • Smart meters are considered to be agents and communicate via MAS;. • The proposed method provides a fast and efficient technique for fault section estimation in distribution systems. Multi-Agent Systems (MAS) are seen from different areas as one of the paramount trends for the next generation of power systems. Numerous published studies about MAS discuss its utilization in power distribution networks but none focuses on the prior step to restoration and self-healing that is fault section estimation. This paper aims to show how MAS can improve the utilities' reliability indexes and consumer satisfaction by overcoming the multiple fault section estimation problem. In order to do this, the authors considered using MAS as a means of communication between smart meters. The purpose of smart meters usage is to employ devices that are already present in smart grids, mainly because of their reading and saving data capacity. The proposed method was tested on a radial feeder generated by the authors. The network was built on HYPERSIM, a software platform of OPAL-RT Technologies. The simulation results show that this MAS provides speed, efficiency, and automation for the process of fault section estimation. [ABSTRACT FROM AUTHOR]

Abstract: Fault resistance is a critical component of electric power systems operation due to its stochastic nature. If not considered, this parameter may interfere in fault analysis studies. This paper presents an iterative fault analysis algorithm for unbalanced three-phase distribution systems that considers a fault resistance estimate. The proposed algorithm is composed by two sub-routines, namely the fault resistance and the bus impedance. The fault resistance sub-routine, based on local fault records, estimates the fault resistance. The bus impedance sub-routine, based on the previously estimated fault resistance, estimates the system voltages and currents. Numeric simulations on the IEEE 37-bus distribution system demonstrate the algorithm’s robustness and potential for offline applications, providing additional fault information to Distribution Operation Centers and enhancing the system restoration process. [Copyright &y& Elsevier]

Abstract: Underground distribution systems are normally exposed to permanent faults, due to specific construction characteristics. In these systems, visual inspection cannot be performed. In order to enhance service restoration, accurate fault location techniques must be applied. This paper describes an extended impedance-based fault location algorithm for underground distribution systems. The formulation is developed on phase frame and calculates the apparent impedance using only local voltage and current data. The technique also provides an iterative algorithm to compensate the typical capacitive component current of underground cables. Test results are obtained from numerical simulations using a real underground distribution feeder data from the Electrical Energy Distribution State Company of Rio Grande do Sul (CEEE-D), southern Brazil. Comparative results show the techniques accuracy and robustness in respect to fault type, distance and resistance. [Copyright &y& Elsevier]

• Data-driven time-domain protection method based on Support Vector Machine. • Machine learning-based protection scheme implemented in hardware. • Energization events, internal and external faults real-time classification. • Proposed method was scarcely affected by CT saturation. • External-to-internal evolving fault identification. This paper presents a power transformer differential protection scheme based on support vector machines (SVM) combined with high-frequency features extracted with the real-time boundary stationary wavelet transform (RT-BSWT). SVM models are derived with synthetic data, considering a wide variety of events, such as inter-turn faults, external faults during CT saturation, and evolving external-to-internal faults. A comparative performance assessment is carried out considering accuracy and other reliability indices, as well as operating time, and good results were achieved. The simplicity of the presented SVM-based relay, without hard-to-derive parameters, built on the classical differential protection framework, highlights potential aspects towards real-life implementation. [ABSTRACT FROM AUTHOR]

• PDE-based nonlinear controller capable of compensating unknown time-varying delay. • Control action of secondary energy sources for optimal coordination. • Minimizing the disutility of the controller action through Lagrangian relaxation. • Robust to errors in mean estimation of latency. • Simulations show contribution of controller in transient stability enhancement. In this paper, we present a robust Partial Differential Equation-based (PDE) control strategy, which can optimally control both distributed energy storage systems and photovoltaic power plants to enhance the stability margins of synchronous generators. The amount of power that is injected or absorbed from each local power source is determined by a coordination layer, which is implemented by solving a constrained optimization problem that minimizes the cost of the controller action by Lagrangian relaxation. The presented nonlinear controller is robust to unknown time-varying delay and uncertainties on measurements. A time delay compensation technique is developed to inject delay-free control signal into the closed-loop system. Lyapunov-based stability analysis shows that all tracking error signals are globally uniformly ultimately bounded. The proposed method is implemented on IEEE 39-Bus Test System to demonstrate the success of proposed control framework in restoring system stability after being subjected to a large disturbance. [ABSTRACT FROM AUTHOR]