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High impedance faults present unique challenges for power system protection engineers. The first challenge is the detection of the fault, given the low current magnitudes. The second challenge is to locate the fault to allow corrective measures to be taken. Corrective actions are essential as they mitigate safety hazards and equipment damage. The problem of high impedance fault detection and location is not a new one, and despite the safety and reliability implications, relatively few efforts have been made to find a general solution. This work presents a hybrid data driven and analytical-based model for high impedance fault detection in distribution systems. The first step is to estimate a state space model of the power line being monitored. From the state space model, eigenvalues are calculated, and their dynamic behavior is used to develop zones of protection. These zones of protection are generated analytically using machine learning tools. High impedance faults are detected as they drive the eigenvalues outside of their zones. A metric called eigenvalue drift coefficient was formulated in this work to facilitate the generalization of this solution. The performance of this technique is evaluated through case studies based on the IEEE 5-Bus system modeled in Matlab. Test results are encouraging indicating potential for real-life applications. [ABSTRACT FROM AUTHOR]

In the modern power system networks, grid observability has greatly increased due to the deployment of various metering technologies. Such technologies enhanced the real-time monitoring of the grid. The collection of observations are processed by the state estimator in which many applications have relied on. Traditionally, state estimation on power grids has been done considering a centralized architecture. With grid deregulation, and awareness of information privacy and security, much attention has been given to multi-area state estimation. Considering such, state-of-the-art solutions consider a weighted norm of residual measurement model, which might hinder masked gross errors contained in the null-space of the Jacobian matrix. Towards the solution of this, a distributed innovation-based model is presented. Measurement innovation is used towards error composition. The measurement error is an independent random variable, where the residual is not. Thus, the masked component is recovered through measurement innovation. Model solution is obtained through an Alternating Direction Method of Multipliers (ADMM), which requires minimal information communication. The presented framework is validated using the I E E E 14 and I E E E 118 bus systems. Easy-to-implement model, build-on the classical weighted norm of the residual solution, and without hard-to-design parameters highlight potential aspects towards real-life implementation. [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]

In this brief is presented an extension of the Gauss approach for the solution of an overdetermined set of algebraic non linear equations. Further, it is shown that the measurement error, in the Gauss approach, is in the measurement direction and that error has a unique decomposition: 1) the first component, which is orthogonal to the Jacobian range space, the residual and 2) the other which is on the Jacobian range space. The latter is hidden in the Jacobian space when one minimizes the residual. The extension of the Gauss approach is then in the sense to minimize the norm of the error. In engineering, the measurements may have gross errors, and then detection, identification, and correction of those errors are necessary. The Largest Normalized Error Test will be developed for that purpose. Considering the cyber-attack possibility, modeled as a malicious data attack, the error correction step is paramount. Applications on power networks will be used to show the hidden error component when using the Gauss minimization, and also to illustrate all the steps of the presented procedure as well as comparison to the current Gauss approach. [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]

Increasing deployment of information technologies and low-inertia renewable energy sources into smart grid fuel the uncertainties and reveal security and transient stability problems. Enhancing the stability margins of smart grids despite the cyber and physical disturbances emerges the need for cyber-aware robust controller design. Therefore, a distributed nonlinear robust controller is proposed to improve the transient stability margins of synchronous generators (SG) in the presence of excessive communication delay and cyber-physical disturbances. The proposed controller uses phasor measurement units to receive real-time measurements and actuates distributed storage systems to inject or absorb power in order to accelerate stabilization of frequency oscillations of SG following a disturbance. The communication dependency exposes time delay and cyber-security issues since latency is inherent and can be excessive during an attack such as denial of service. In addition, uncertainties in measurements challenge the stabilization process. Hence, the proposed controller is designed for robustness to delay and additive disturbances. A novel time delay compensation technique is developed to inject delay-free control signal into the closed-loop system. To guarantee that all tracking error signals are globally uniformly ultimately bounded, novel Lyapunov–Krasovskii functionals are used in the Lyapunov-based stability analysis. The simulation results validate the feasibility of the proposed control framework and robustness under cyber-physical practical limitations. [ABSTRACT FROM PUBLISHER]

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]

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]

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]

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]

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]

• 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]