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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]

Due to global climate change, the effect of extreme weather on power systems has attracted extensive attention. In the prior-art grid resilience studies, the hurricanes or wildfires are mainly defended in terms of expected line damages, while they are prone to trigger short-circuit fault (SCF) evolved with dynamic influence in reality. In this paper, a fragile model is developed to evaluate the nodal SCF probability considering the insulation aging of equipment and extreme weather condition. Then, a response framework for extreme weather events is developed for a transmission system to defend the cascading impacts of expected SCFs. Specifically, switches are shifted to restrain the out-of-range short-circuit currents (SCCs) so that to ensure the SCFs can be removed by circuit breakers, generation rescheduling and load shedding are arranged to maintain the post-fault system transient stability. The above measures are optimized simultaneously by an integrated Mixed-Integer Nonlinear Programming (MINLP). Considering the error or uncertainty of weather event forecasts, a multi-state model is established to provide the most cost-effective grid resilience enhancement scheme, in which the expected urgent adaptions of the initial scheme subject to weather state transition is included in the overall cost. The proposed model and techniques are validated using the IEEE 39-bus New-England test system and realistic meteorological data. [ABSTRACT FROM AUTHOR]

Growing integration of wind power and increasing use of induction motor loads dramatically affect a power system's dynamic performance. To address the challenges, this paper proposes a robust dynamic VAR planning method to enhance the voltage stability of wind energy power systems under uncertainty. Firstly, two indices are developed to evaluate the steady-state and the short-term voltage stability of the system. Then, a robustness index is proposed to quantitatively evaluate the robust optimality of the solutions, considering the uncertainties from wind power output and STATCOMs initial state before a contingency. Four objectives are optimized simultaneously: 1) total planning cost, 2) short-term voltage stability index, 3) steady-state voltage stability index, and 4) robustness of the solutions. Finally, an Adaptive Non-dominated Sorting Genetic Algorithm-III based on Latin Hypercube Sampling (A-NSGA-III-LHS)is designed to solve this many-objective optimization problem with 3 improvements over the standard NSGA-III: 1) adaptive mutation rate, 2) Differential Evolution operator, 3) Latin Hypercube Sampling based initial population generation. The proposed method is tested on the New England 39-bus system with an industry-standard complex load model, showing high robust optimality and computational efficiency over conventional methods. [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]

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]

This paper presents a novel approach to damp interarea oscillations by designing a robust multi-input multioutput supplementary controller for multiterminal dc (MTDC) systems embedded in ac grids. The key idea to achieve robustness lies in explicitly modeling the MTDC current injection as disturbances using an \mathcal H\infty mixed-sensitivity formulation in the linear matrix inequality framework. Control directions are established by selecting wide-area feedback signals and the relative gain array computation. Robustness is assessed through dynamic simulations for scenarios including: first, disturbances on the ac side, second, disturbances on the dc-side such as loss of a converter pole including actuator, third, partial loss of feedback signal, and fourth, communication latencies. The performance of the proposed controller is compared against the conventional \mathcal H\infty based design, using a four-terminal dc grid embedded within the New England–New York test system. The results suggest that the proposed approach demonstrates superior performance following dc-side disturbances, actuator outages, and latency. [ABSTRACT FROM PUBLISHER]