Navin Bhatt

Next-Generation Monitoring, Analysis, and Control for the Future Smart Control Center

This paper proposes a vision of next-generation monitoring, analysis, and control functions for tomorrows smart power system control centers. The paper first reviews the present control center technology and then presents the vision of the next-generation monitoring, analysis, and control functions. The paper also identifies the technology and infrastructure gaps that must be filled, and develops a roadmap to realize the proposed vision. This smart control center vision is expected to be a critical part of the future smart transmission grid.

Decision Tree-Based Online Voltage Security Assessment Using PMU Measurements

Voltage collapse is a critical problem that impacts power system operational security. Timely and accurate assessment of voltage security is necessary to detect post-contingency voltage problems in order to prevent a large scale blackout. This paper presents an online voltage security assessment scheme using synchronized phasor measurements and periodically updated decision trees (DTs). The DTs are first trained offline using detailed voltage security analysis conducted using the past representative and forecasted 24-h ahead operating conditions. The DTs are also updated every hour by including newly predicted system conditions for robustness improvement. The associated synchronized critical attributes are obtained in real time from phasor measurement units (PMUs) and compared with the offline thresholds determined by the DTs to assess security. This approach is tested on the American Electric Power (AEP) system and properly trained DTs perform well in assessing voltage security. Several new ideas to improve DT performance are also introduced.

Dynamic Optimization Based Reactive Power Planning to Mitigate Slow Voltage Recovery and Short Term Voltage Instability

Short term voltage stability poses a significant threat to system stability and reliability. This paper applies dynamic VAr injection to ensure short term voltage stability following a large disturbance in a power system with high concentration of induction motor loads. Decelerating and stalling of induction motor loads is considered to be the major cause of fault induced delayed voltage recovery (FIDVR) and short term voltage stability. If system dynamics are not taken into account properly, the proposed control solution may be an expensive over design or an under design that is not capable of eliminating FIDVR problems completely. In this work, the optimal amount and locations for installing dynamic reactive resources are found by control vector parameterization (CVP), a dynamic optimization approach. The efficiency and effectiveness of this approach is improved by utilizing results from trajectory sensitivity analysis, singular value decomposition and linear programming optimization. Dynamic optimization based on CVP approach is tested in an IEEE 162-bus system and a realistic large scale utility power system.

An algorithm for removing trends from power-system oscillation data

When analyzing the electromechanical dynamic properties of power-system field-measurement data using signal processing techniques, it is often useful to identify and remove the slow trends within the data. This paper proposes an iterative non-linear trend identification algorithm. The proposed method adapts the upper and lower envelope idea proposed by empirical mode decomposition (EMD) method to identify the trend. The comparison with conventional trend identification methods are made with simulation data. Also, the proposed algorithm is applied to a field measurement data set to evaluate its performance.

Assessing vulnerability to cascading outages

This paper addresses the testing and implementation of a fast process for sequential contingency simulation in order to identify potential cascading modes due to thermal overloads. It also presents computation of the vulnerability index of cascading, based on the estimated likelihood and consequences of cascading outages. The approach described in this paper offers a unique capability to automatically identify initiating events that may lead to cascading outages. It predicts the development of cascading events by automatically identifying and visualizing potential cascading tiers. The proposed approach was implemented using a 50,000-bus Eastern Interconnection power system network. The results of the study indicate that initiating events and possible cascading chains may be quickly identified, ranked and visualized in on-line and offline environments. This approach may be used to improve the reliability of a transmission grid and reduce its vulnerability to cascading outages. It may be added to the existing contingency analysis tools to assess the impact of cascading events in both on-line and off-line environments.

ARMAX-Based Transfer Function Model Identification Using Wide-Area Measurement for Adaptive and Coordinated Damping Control

One of the main drawbacks of the existing oscillation damping controllers that are designed based on offline dynamic models is adaptivity to the power system operating condition. With the increasing availability of wide-area measurements and the rapid development of system identification techniques, it is possible to identify a measurement-based transfer function model online that can be used to tune the oscillation damping controller. Such a model could capture all dominant oscillation modes for adaptive and coordinated oscillation damping control. This paper describes a comprehensive approach to identify a low-order transfer function model of a power system using a multi-input multi-output (MIMO) autoregressive moving average exogenous (ARMAX) model. This methodology consists of five steps: 1) input selection; 2) output selection; 3) identification trigger; 4) model estimation; and 5) model validation. The proposed method is validated by using ambient data and ring-down data in the 16-machine 68-bus Northeast Power Coordinating Council system. The results demonstrate that the measurement-based model using MIMO ARMAX can capture all the dominant oscillation modes. Compared with the MIMO subspace state space model, the MIMO ARMAX model has equivalent accuracy but lower order and improved computational efficiency. The proposed model can be applied for adaptive and coordinated oscillation damping control.

Measurement-Based Real-Time Voltage Stability Monitoring for Load Areas

Summary form only given. This paper proposes a measurement-based voltage stability monitoring method for a load area fed by N tie lines. Compared to a traditional Thevenin equivalent based method, the new method adopts an N+1 buses equivalent system so as to model and monitor individual tie lines. For each tie line, the method solves the power transfer limit against voltage instability analytically as a function of all parameters of that equivalent, which are online identified from real-time synchronized measurements on boundary buses of the load area. Thus, this new method can directly calculate the real-time power transfer limit on each tie line. The method is first compared with a Thevenin equivalent based method using a four-bus test system and then demonstrated by case studies on the NPCC (Northeast Power Coordinating Council) 48-machine, 140-bus power system.

An adaptive three-bus power system equivalent for estimating voltage stability margin from synchronized phasor measurements

This paper utilizes an adaptive three-bus power system equivalent for measurement-based voltage stability analysis. With that equivalent identified online, a measurement-based approach is developed to estimate real-time voltage stability margin for a load-rich area supported by remote generation via multiple tie lines. Compared with traditional Thevenin equivalent based approach, this new approach is able to provide more accurate voltage stability margin for each individual tie line. This approach is validated on a three-bus system and the IEEE 39-bus system.

Preliminary synchronized phasor data analysis of disturbance events in the US Eastern Interconnection

This paper presents analysis results of synchronized phasor data from 10 disturbance events recorded in the US Eastern Interconnection (EI). The phasor data covers a wide region in the EI, allowing for the study of disturbance propagation, interarea modes, and oscillations in voltages and currents. The analysis is not straightforward because the EI is a meshed system with adequate interarea mode damping. Disturbances involving tripping a single large generator unit produce very short interarea swing responses. Islanding events involving regions at the perimeter, however, provide more prominent responses for analysis.

The Rockport plant-analysis of temporary fast turbine valving tests

Temporary fast turbine valving (TFTV) field tests were carried out on AEPs 1300 MW Rockport unit. Tests at various unit loading levels verified the functional aspects of the TFTV scheme, including the control and intercept valve-stroke characteristics and the rapid reduction of mechanical driving power. An analysis of the mechanical and electrical performance characteristics of the Rockport unit during TFTV is presented. A comparison of the test measurements with digital simulation results is provided to validate the simulation tools and models commonly used in system dynamics studies. >