Feifei Bai

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.

Investigation on Impacts of Alternative Generation Siting in Power Grids from the View of Complex Network Theory

Abstract In this article, the impacts of alternative generation integration in a power grid are discussed from the view of complex network theory. Using the improved complex network index, the structural performance of the system could be assessed in planning. Also, the distribution of load and generation are also considered in the modeling. Compared with the existing planning method, the proposed method can not only solve alternative generation units siting issues but also locate the corresponding conventional generation to be curtailed or replaced. Furthermore, as more information is obtained, e.g., related policy or cost parameters, a multi-objective comprehensive decision model is designed, the weight coefficient of which is determined by the two-tuple linguistic decision method. The proposed indices and models can effectively realize fast location and help improve the structural performance of the system with appropriate alternative generation integration. The models and methods are tested and verified by test cases.

Measurement-based power system frequency dynamic response estimation using geometric template matching and recurrent artificial neural network

Understanding power system dynamics after an event occurs is essential for the purpose of online stability assessment and control applications. Wide area measurement systems (WAMS) based on synchrophasors make power system dynamics visible to system operators, delivering an accurate picture of overall operating conditions. However, in actual field implementations, some measurements can be inaccessible for various reasons, e.g., most notably communication failure. To reconstruct these inaccessible measurements, in this paper, the radial basis function artificial neural network (RBF-ANN) is used to estimate the system dynamics. In order to find the best input features of the RBF-ANN model, geometric template matching (GeTeM) and quality-threshold (QT) clustering are employed from the time series analysis to compute the similarity of frequency dynamic responses in different locations of the power system. The proposed method is tested and verified on the Eastern Interconnection (EI) transmission system in the United States. The results obtained indicate that the proposed approach provides a compact and efficient RBF-ANN model that accurately estimates the inaccessible frequency dynamic responses under different operating conditions and with fewer inputs.

Methods to establish input-output relationship for system identification-based models

Both model-based and measurement-based methods are presented in this paper to describe the correlation between measurement locations. Transfer impedance (the model-based method) and correlation coefficient (the measurement-based method) are compared and applied to input location selection of power system dynamic modeling for dynamic response estimation. The comparison results show that both methods can describe the correlation between measurement locations effectively.

Input signals selection for measurement-based power system ARX dynamic model response estimation

This paper proposes a measurement-based approach to optimize the inputs of Auto-Regressive with eXogenous input (ARX) model identification in large power systems. Correlation Coefficient Index (CCI) is defined in this paper and Correlation Coefficient Map (CCM) is developed for the US Eastern Interconnection (EI) to show the correlation between any two power system output measurement signals visually. This approach is verified with EI system simulation data and applied to Frequency Disturbance Recorder (FDR) measurement data to estimate system dynamic response. The verification result shows that the number of ARX model inputs can be decreased and the estimation accuracy can be ensured by using the proposed approach.

A measurement-based control input-output signal selection approach to damp inter-area oscillations

Wide-area measurement systems enable the wide-area damping controller (WADC) to use remote signals to enhance the small signal stability of large scale interconnected power systems. Due to the global properties, conventional control input-output selection approach based on the detailed mathematical models are not available for the complicated systems. A new measurement-based damping control input- output signal selection approach is proposed based on the residue of a constructed linear autoregressive exogenous (ARX) model, which is applied to derive a low-order black-box transfer function model of a power system with power system stabilizers (PSSs) using wide-area signals. Fast Fourier transform (FFT) analysis is performed to preselect the feedback signals at the dominant mode for ARX model construction. Based on the identified ARX model, the residue is used to select the optimal control input-output pairs. Finally, the selected control input- output signal pair is verified by the control performance comparison in a 16-machine 68-bus power system.

A New Remote Tap Position Estimation Approach for Open-Delta Step-Voltage Regulator in a Photovoltaic Integrated Distribution Network

With the rapid development of photovoltaic (PV) technology, more utility-scale PV systems are being integrated into rural areas where abundant and low-cost land is available. In these areas, step-voltage regulators (SVRs) with an open-delta configuration are widely used for voltage regulation. However, since SVRs were initially designed for tackling slow and smooth load variations, frequent PV output fluctuations can cause excessive tap changes. Moreover, rural communication facilities are normally expensive and underdeveloped, so only limited parameters are recorded with low resolution and reliability. Thus, much needed tap information cannot be properly monitored in a cost-effective way. In contrast, a downstream load center or utility-scale PV site is commonly well equipped with modern sensors and data acquisition systems, which provide the possibility for tap evaluation. Therefore, this paper proposes a new remote tap position estimation approach to accurately assess the upstream tap positions of open-delta SVRs from downstream measurements. Furthermore, the proposed approach is firmly validated through field testing under the support of the local utility and PV plant owner. This novel method not only enables reliable tap position monitoring with high precision for utilities to research PV–SVR interaction, but also provides valuable information to PV owners for correctly analyzing downstream voltage performance.

The Anatomy of the 2016 South Australia Blackout: A Catastrophic Event in a High Renewable Network

Over the last decade, many power systems have significantly changed with the proliferation of renewable generation sources, such as wind and solar photovoltaic. Due to their variability and nonsynchronous nature, new challenges and complexities have emerged regarding operational security of modern power systems. The 2016 South Australia (SA) blackout was the first known blackout due to such a high renewable situation. An official report has recently been published to review the causes and provide the corresponding recommendations for improvement of network operation, control, and security. However, there are still a number of critical issues and debates which remain unsolved, such as network bottleneck identification, overvoltage explanation, pole slip concern, frequency dip mystery, and frequency/voltage instability debate. In this paper, based on the reconstruction of the event, these unsettled issues are prudently analyzed to unveil their root causes. In addition, an innovative scheme is proposed to prevent the blackout by identifying the network separation at an early stage. This research will not only further advance the understanding of the 2016 SA blackout, but also will provide valuable guidelines for the management of future renewable-rich networks.

A simulation-based linearity study of large-scale power systems

The power system is a typical complex and nonlinear system in nature. Theoretically, the nonlinear approach can describe a dynamic system more accurately than a linear approach, but to an actual power grid, a linear approach was usually used to model a nonlinear problem approximately. To investigate when the system can be linearized and “how small is small” to linearize the system accurately, this paper proposed a measurement-based linearity study approach based on the linear system theory, which utilizes the dynamic responses after events in the actual U.S. Estern Interconnection (EI) power grid and the North-Central China power grid.