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This paper develops a systematic framework for analyzing how low frequency forced oscillations propagate in electric power systems. Using this framework, the paper shows how to mathematically justify the so-called Dissipating Energy Flow (DEF) forced oscillation source location technique. The DEF's specific deficiencies are pinpointed, and its underlying energy function is analyzed via incremental passivity theory. This analysis is then used to prove that there exists no passivity transformation (i.e. quadratic energy function) which can simultaneously render all components of a lossy classical power system passive. The paper goes on to develop a simulation-free algorithm for predicting the performance of the DEF method in a generalized power system, and it analyzes the passivity of three non-classical load and generation components. The proposed propagation framework and performance algorithm are both tested and illustrated on the IEEE 39-bus New England system and the WECC 179-bus system. [ABSTRACT FROM AUTHOR]

Series compensation is used to improve power system transmission capacity. Subsynchronous resonance (SSR) associated with such a system is a challenging issue. Today, with increasing integration of wind farm (WF) to power network, the stability of the system gets deteriorated due to variation in wind speed at the WFs. The reaction between the SSR modes and the doubly fed induction generator converters is known as subsynchronous control interaction (SSCI), due to which, it becomes more challenging to achieve power system stability. To overcome these issues, in this paper, a synchrophasor data-based control (SDC) technique is proposed. The proposed controller diminishes induction generator effect, torsional interaction, and the SSCI effect on the series compensated network, integrating multiple WFs. The SDC provides an auxiliary SSR damping control (SSRDC) with thyristor controlled series compensation (TCSC). This SSRDC uses synchrophasor data from WF connected point of common couplings (PCCs) inside the grid to improve the SSR oscillation damping. The proposed method maintains reference voltage angle of the PCCs by controlling equivalent impedance of the grid. The impedance provides significant damping for SSR along with the TCSC control. The proposed SDC is tested for modified 39-bus New England system with WFs and is found to be effective. Comparison of this method with conventional local control demonstrates its superior performance. [ABSTRACT FROM AUTHOR]

Distance relays are quite vulnerable to maloperation during dynamic stressed situations. The apparent impedance seen by the relay encroaches the zone-3 resulting in distance relay maloperation that can initiate cascading failures. This paper presents an enhanced scheme for wide area backup protection which implements improved protection algorithms to decide final relaying status. A machine learning tool namely Deep Neural Network is utilized to build those protective relaying decision logics: RDL-1 and RDL-2. Wide area information retrieved from phasor measurement units (PMU) is used to take real time decisions. RDL-1 is designed to detect if the system is operating in normal or stressed condition. During normal state, traditional zone-3 relay undertakes the relaying decision. However, under stressed situations, RDL-1 switches the decision-taking to RDL-2. RDL-1 also predicts whether the system is progressing towards an out-of-step situation so that appropriate remedial action can be undertaken. Proposed scheme was studied on IEEE-39 bus New England system using MATLAB/SIMULINK and validated on Real Time Digital Simulator platform and third zone mal-tripping are avoided. Performance of the proposed algorithm was compared with the conventional blinder and other data-mining techniques which show considerably high classification accuracy. [ABSTRACT FROM AUTHOR]

System inertia plays a vital role in controlling the angular stability of the system during a disturbance. Due to increased penetration of power electronic interfaced sources, such as Solar Photovoltaic (SPV) source, the overall system inertia reduces and varies depending on their operating conditions. In this paper, an approach for online inertia estimation in the power system network with SPV sources is proposed, using the synchronized measurements from Phasor Measurement Units (PMUs). An equivalent swing equation is used to emulate the network dynamics. A relationship between the inertia constant and the roots of this equation is determined. In order to numerically obtain the roots, the Estimation of Signal Parameter via Rotational Invariance Techniques (ESPRIT) method is first used to find the modes present in the frequency signal. A new formulation is proposed to extract an equivalent mode from all the obtained modes. Also, to avoid phase step error, Rate Of Change Of Frequency (ROCOF) is estimated from the equivalent mode of the frequency signal. Results obtained for the 39 bus New England system for various test cases, using Real-Time Digital Simulator (RTDS), prove the efficacy and superiority of the proposed approach over the existing approaches in the literature. [ABSTRACT FROM AUTHOR]

This paper presents a power swing detection algorithm in multi-machine power systems, which uses wide-area synchrophasor measurements and is based on Zubov’s stability boundaries. Zubov’s boundary method, an approximation of the famous Lyapunov function, is very common for numerical analyses of power system stability. This work extends the concept of Zubov’s approximation boundaries to online protection applications. First, the proposed protection algorithm constructs a series of Zubov’s stability boundaries on power angle–frequency ($\delta$ – $\omega$) plane for generators based on real-time measurements from phasor measurement units/merging units. Then, it tracks the trajectory of each generator in the $\delta$ – $\omega$ plane after the disturbance to differentiate out-of-step (OOS) conditions from stable swings. The proposed approach is suitable for online applications, which is a significant improvement over the existing methods for swing detection since it does not require offline studies and network reduction. Effectiveness of the proposed method is shown using a single-machine infinite bus and New-England 10-machine 39-bus systems. The proposed method is also implemented in a hardware-in-the-loop setup with a customized IEC 61850-based OOS relay, and performance is compared with a commercially available relay. [ABSTRACT FROM AUTHOR]

Poorly damped inter-area modes of oscillations represent a major concern to power system operation since they detain the power transfer capability of transmission networks. This situation becomes more stringent as the tie-lines are heavily stressed and/or large amounts of renewable energy resources are installed. To overcome this issue, a detailed mathematical model is proposed in this paper to reduce the linearized model of a large power system using the cross-Gramian technique. The presented approach divides the system into a study area which contains one generation unit with installed power system stabilizer (PSS) and an external one which comprises the rest of generation units in the system. Model order reduction is only applied to the external area with the objective of maintaining the characteristics of the original model. Meanwhile, the dynamics of the study area are preserved to provide the required damping through the designed PSS. In addition, an online tuning methodology is also presented to provide robust damping performance in response to changes in the system operating conditions. The deployed cross-Gramian model order reduction alleviates the computational burden and time associated with the online PSS tuning when original power system models are used. The effectiveness of the proposed approach is tested using the New-England 39-bus system in addition to another practical system which resembles the Northern Regional Power Grid India test system. [ABSTRACT FROM AUTHOR]

This paper presents a method for detecting and correcting malicious data corruptions in phasor measurement unit (PMU) measurements. Detection of malicious injections is formulated as a compressed sensing problem and the actual signals are recovered using an online robust principal component analysis-based algorithm. Different patterns of malicious injection attacks on PMU data are considered and the effect of corruption and reconstruction using the algorithm is analyzed on a wide-area mode metering application. The performance of the proposed algorithm has been evaluated with different subspace selection. A suitable threshold for the algorithm is selected by a graphical analysis of the receiver operating characteristics curve. Data from a 16-machine, 5-area New England–New York system is used along with a recursive modal estimation algorithm to validate the effectiveness of the proposed approach under ambient and transient conditions. [ABSTRACT FROM AUTHOR]

With a high proportion of new energy and power electronic equipment connected to the modern power system, a new type of subsynchronous oscillation (SSO) is triggered, which affects the safe and stable operation of the system. Accurate analysis and identification of the SSO source becomes the key to studying this problem. This article presents a novel method to analyze SSOs. First, multisynchrosqueezing transform is applied to the signal to get the concentrated time–frequency analysis results. Then, the ridge tracking method is utilized to identify and reconstruct the subsynchronous component signals. The method of dissipating energy flow is applied to locate the source and sink of the SSO in the subsynchronous component signals. The performances of the proposed method are verified using electromagnetic transient simulations in a three-wind farms system and a modified IEEE 10-generator 39-bus New England power system. [ABSTRACT FROM AUTHOR]

This letter proposes an online control strategy to enhance the overall damping of low-frequency power system oscillations of large inter-connected electrical networks. To achieve this objective, the proposed approach employs wide area measured signals to estimate an accurate online model of power system dynamics using the dynamic mode decomposition with control (DMDc) method. The DMDc technique applies singular value decomposition (SVD) to the collected data matrices such that an accurate low-order approximation of system dynamics is obtained. The estimated model is thereafter utilized in designing the wide area damping controller (WADC) using discrete linear quadratic regulator (DLQR). Furthermore, kalman filtering is deployed to update the states of the designed controller and to remove the noise that is contained in the measured signals. The effectiveness of the proposed method is tested on the 10 machines, 39-bus New England test system. [ABSTRACT FROM AUTHOR]

An identification algorithm is proposed for generator outages in external systems given tie-line flow measurements and pre-outage linear sensitivity factors. The problem is challenging due to limited information available to operators in interconnected systems. To overcome the underdetermined nature of the problem (the number of tie-line measurements is smaller than the number of generators), a clustering method based on pivoted QR decomposition is implemented so that the outage location can be identified to the area of origination. Two test systems, the 68-bus New England system and the 500-bus synthetic system, were used for validation. The results demonstrate that with limited knowledge of the external system, the algorithm is able to identify the correct generator cluster in all cases. Another advantage of the proposed algorithm is its high efficiency, which enables detection within sub-milliseconds. In addition, an estimation of the cluster injection change is also provided by the algorithm. [ABSTRACT FROM AUTHOR]