Large Interconnected Power Grid Research Articles

Critical zone identification framework for bulk electric system security assessment

Climate change introduces a new set of vulnerabilities. It might cause unexpected voltage and frequency violation problems that can damage the existing power system configurations. Identifying the zones containing more critical violations in a bulk system under different climatic conditions and contingencies is crucial to securing the power system operation and infrastructure safety. This paper presents an advanced critical zone identification framework that can retrieve information from extensive data yielded by dynamic contingency analysis results from a large interconnected power grid. A machine learning (ML) based clustering approach is applied to identify the critical zone under hundreds of scenarios. The developed framework is tested using the 2028 western electricity coordinating council (WECC) system, and the detailed results are discussed in this paper.

Deep Learning-Based Adaptive Remedial Action Scheme with Security Margin for Renewable-Dominated Power Grids

The Remedial Action Scheme (RAS) is designed to take corrective actions after detecting predetermined conditions to maintain system transient stability in large interconnected power grids. However, since RAS is usually designed based on a few selected typical operating conditions, it is not optimal in operating conditions that are not considered in the offline design, especially under frequently and dramatically varying operating conditions due to the increasing integration of intermittent renewables. The deep learning-based RAS is proposed to enhance the adaptivity of RAS to varying operating conditions. During the training, a customized loss function is developed to penalize the negative loss and suggest corrective actions with a security margin to avoid triggering under-frequency and over-frequency relays. Simulation results of the reduced United States Western Interconnection system model demonstrate that the proposed deep learning–based RAS can provide optimal corrective actions for unseen operating conditions while maintaining a sufficient security margin.

A Comprehensive Method to Mitigate Forced Oscillations in Large Interconnected Power Grids

Multiple severe forced oscillation events have recently been observed across the North American interconnections and around the world. These forced oscillations have caused power swings, limited power transfer capability, damaged equipment, and persisted indefinitely until the driving source was located and removed. This paper proposes a comprehensive method to mitigate forced oscillations. Once a forced oscillation is detected, a new source location algorithm can be used to locate the source based on the oscillation mode angle without requiring system topology information. If the source cannot be quickly located and removed, a control strategy can be activated to modulate the active power of utility-scale inverter-based battery energy storage systems (BESSs) to reduce the energy of forced oscillations to a safe level and allow sufficient time for locating the exact source. The proposed source location algorithm is validated using measurements collected during the January 11, 2019 forced oscillation event in North America and other actual grid events, while the proposed control strategy is verified using the Eastern Interconnection dynamic model under the replicated January 11, 2019 forced oscillation event. The simulation results demonstrated that the proposed source location algorithm can accurately identify the forced oscillation source, and the proposed control strategy can significantly reduce forced oscillation energy.

Improving Power System State Estimation Based on Matrix-Level Cleaning

Power system state estimation is heavily subjected to measurement error, which comes from the noise of measuring instruments, communication noise, and some unclear randomness. Traditional weighted least square (WLS), as the most universal state estimation method, attempts to minimize the residual between measurements and the estimation of measured variables, but it is unable to handle the measurement error. To solve this problem, based on random matrix theory, this paper proposes a data-driven approach to clean measurement error in matrix-level. Our method significantly reduces the negative effect of measurement error, and conducts a two-stage state estimation scheme combined with WLS. In this method, a Hermitian matrix is constructed to establish an invertible relationship between the eigenvalues of measurements and their covariance matrix. Random matrix tools, combined with an optimization scheme, are used to clean measurement error by shrinking the eigenvalues of the covariance matrix. With great robustness and generality, our approach is particularly suitable for large interconnected power grids. Our method has been numerically evaluated using different testing systems, multiple models of measured noise and matrix size ratios.

Online Coherency Based Adaptive Wide Area Damping Controller for Transient Stability Enhancement

This paper proposes a novel wide-area control strategy to enhance the transient stability of a large inter-connected power grid. The proposed control strategy achieves maximal damping of the inter-area oscillations by calculating the optimal number of cluster centers based on a novel online coherency grouping. To achieve this objective, the critical electro-mechanical mode is selected using localness index method during transient conditions. In addition, the online identification of the full model is performed to estimate the states to be controlled during the grid disturbances. Thereafter, a discrete linear quadratic regulator (DLQR) is directly applied to the estimated states, and the corresponding signals are channelized through the loop of most controllable and observable machines of each coherent group. The efficacy of the proposed method is tested on IEEE 39 bus and IEEE 68 bus standard benchmark model. The results demonstrate faster damping with minimal computation burden compared to existing solutions such as a classical slow coherency and a multi-input multi-output (MIMO) based wide area damping controllers.

Suppressing Intermittent Subsynchronous Oscillation via Subsynchronous Modulation of Reactive Current

Recently, a new oscillation phenomenon—intermittent subsynchronous oscillation (ISSO)—has been observed in a large interconnected power grid. Rather than leading to oscillatory instability, ISSO causes cumulative fatigue damage and reduces the shaft life of the generator. The existing phase-compensation-based damping technologies are found to be limited in mitigating these types of oscillations. To mitigate ISSO, a subsynchronous modulation of reactive current (SMRC) approach is established and implemented in the voltage-source converters (VSCs) at the generator terminals. The contribution of SMRC to system damping has been analyzed in order to select control parameters for the VSC. The SMRC controller has been prototyped and extensively tested on a real-time closed-loop simulation platform equipped with a newly developed speed sensor module for precisely interfacing the real-time digital simulator with the rotating speed-acquisition board. Extensive experiments on the input and output characteristics of the VSC have been carried out to test and validate the damping current generating module. The effective damping areas are obtained from test observations to fine tune the parameters of the VSC controller for adapting to various system operating conditions, resulting in the common optimal damping region. Real-time simulations, onsite commissioning, and statistics have demonstrated the ability of the SMRC to mitigate ISSO and subsynchronous oscillation in power plants.

Directional weighting based wide area backup protection tripping strategy

Summary The development of large inter-connected power grid poses an urgent need for better adaptability of the backup protection. In this paper, a wide area backup protection tripping strategy based on directional weighting is proposed, on the premise that the fault component has been identified by the limited wide area centralized backup protection. First, according to the network topology and the positive sequence current phasor information of the switches in local area, the node–branch correlation matrix based on directional weighting is formed. And then, based on the fault identification result and the positive sequence current phasor information of the switches, the component–breaker correlation degree vector is constructed, and the correlated breakers are identified and tripped. Simulation results verify that, with the proposed method, the backup protection coordination is simplified and fault clearance could be limited to the minimum range in various cases. Meanwhile, the proposed method is applicable and reliable even when part of the information is missing, and the requirement on information synchronization is not strict. Copyright © 2015 John Wiley & Sons, Ltd.

Research on Security Assessment Index System for Operating Reserve in Large Interconnected Power Grid

Optimization and placement of spinning reserve is an important issue in power system planning and operation. Systematic way for security assessment of operating reserve needs to study. A security assessment index system for operating reserve in large interconnected power grids is presented in this paper. Firstly, classification and determination methods of operating reserve at home and abroad are investigated, and operating reserve is divided into transient state operating reserve and quasi-steady state operating reserve from the view of security assessment. Secondly, assessment indexes and optimization methods for transient state operating reserve are studied. Thirdly, optimization model, deterministic and probabilistic optimization methods for quasi-steady state operating reserve are explored. Finally, some principles for determination of operating reserve are suggested, and a security assessment index system is put forward. The proposed index system, considering both transient and quasi-steady state, both deterministic and probabilistic methods, provides a systematic way to assessment and arrangement of operating reserve.

Generator Fault Tolerance and Grid Codes

In large interconnected power grids, it is incumbent on each generating plant to do its fair share in maintaining the security and reliability of the grid. The ability of a power plant to continue operation after a grid disturbance is governed by 1) the ability of its generator to recover voltage and remain in synchronism with the power grid after the disturbance (i.e., transient stability) 2) the ability of its turbine generator and auxiliary systems to remain in operation during and after the disturbance (i.e., fault ride-through capability).

Coordination of Transmission Path Transfers

The transfer capability on a transmission path is limited by constraints on acceptability, voltage security, small-signal stability, and transient stability. For a large interconnected power grid, these constraints are influenced significantly by the interactions among path flows in different control areas. When a critical transmission path capability is limited by one of these constraints, it may be necessary to coordinate the interarea power transfers so as to improve the transfer capability on the constrained path without compromising on the security criteria. Based on such considerations, this paper presents a novel multiobjective methodology in which global strategies are developed for the improvement and coordination of transmission path transfers. The problem is formulated with respect to various constraints into suitable optimization problems. An efficient nonlinear programming algorithm with sufficient line search step is incorporated for finding optimal solutions while also incorporating security and stability constraints. The MW benefits for the transfer capability from the coordination procedure are explicitly demonstrated after the optimization process. The effectiveness of the methodology is illustrated by case studies on improving the capability of the California-Oregon Intertie (COI) for large-scale WECC western American power system models.