Shutang You

Impact of High PV Penetration on the Inter-Area Oscillations in the U.S. Eastern Interconnection

This study explores the impact of high-photovoltaic (PV) penetration on the inter-area oscillation modes of large-scale power grids. A series of dynamic models with various PV penetration levels are developed based on a detailed model representing the U.S. Eastern Interconnection (EI). Transient simulations are performed to investigate the change of inter-area oscillation modes with PV penetration. The impact of PV control strategies and parameter settings on inter-area oscillations is studied. This paper finds that as PV increases, the damping of the dominant oscillation mode decreases monotonically. It is also observed that the mode shape varies with the PV control strategy and new oscillation modes may emerge under inappropriate parameter settings in PV plant controls.

A Distribution Level Wide Area Monitoring System for the Electric Power Grid–FNET/GridEye

The wide area monitoring system (WAMS) is considered a pivotal component of future electric power grids. As a pilot WAMS that has been operated for more than a decade, the frequency monitoring network FNET/GridEye makes use of hundreds of global positioning system-synchronized phasor measurement sensors to capture the increasingly complicated grid behaviors across the interconnected power systems. In this paper, the FNET/GridEye system is overviewed and its operation experiences in electric power grid wide area monitoring are presented. Particularly, the implementation of a number of data analytics applications will be discussed in details. FNET/GridEye lays a firm foundation for the later WAMS operation in the electric power industry.

Ring-down oscillation mode identification using multivariate Empirical Mode Decomposition

Inter-area oscillation in a large power systems draws much attention because it might severely influence system security and reduce transmission capability. The recent large-scale deployment of phasor measurement units (PMUs) enables online measurement-based monitoring and analysis on inter-area oscillatory modes. However, the nonstationary characteristics of measurements become obstacles for oscillation analysis. This work proposes multivariate empirical mode decomposition (MEMD), a multi-channel time frequency analysis method, for ring-down oscillation mode identification. The capability of the MEMD in oscillation mode identification is verified based on a test system. In addition, MEMD is compared with classical Empirical Mode Decomposition (EMD) and Fast Fourier Transform (FFT) for evaluation. The result shows that MEMD can improve oscillation identification through separating different oscillation modes while persevering their phase and amplitude information.

A survey on next-generation power grid data architecture

The operation and control of power grids will increasingly rely on data. A high-speed, reliable, flexible and secure data architecture is the prerequisite of the next-generation power grid. This paper summarizes the challenges in collecting and utilizing power grid data, and then provides reference data architecture for future power grids. Based on the data architecture deployment, related research on data architecture is reviewed and summarized in several categories including data measurement/actuation, data transmission, data service layer, data utilization, as well as two cross-cutting issues, interoperability and cyber security. Research gaps and future work are also presented.

Data Architecture for the Next-Generation Power Grid: Concept, Framework, and Use Case

To support next-generation power grid monitoring, protection, and control, we re-view and synthesize the new requirements and challenges of the enabling data architecture. We outline the necessary elements and a framework for the data architecture including the data path, synchronization and alignment layer, high-speed stream processing, databases, data service layer, and the interaction with analytics & control applications. We select and discuss wide-area damping control, a representative real-time closed-loop control application, as a use case to demonstrate the proposed data architecture.

Non-Invasive Identification of Inertia Distribution Change in High Renewable Systems Using Distribution Level PMU

This letter proposed an approach to identify the change of inertia distribution in high renewable power systems. Using the footprints of electromechanical wave propagation at the distribution level, this approach provides a new and non-invasive way to aware the system inertia distribution for primary frequency response. Actual measurements and high renewable dynamic models validated effectiveness of the approach.

Frequency Response Assessment and Enhancement of the U.S. Power Grids Toward Extra-High Photovoltaic Generation Penetrations—An Industry Perspective

Nonsynchronous generators such as photovoltaics (PVs) are expected to undermine bulk power systems (BPSs)’ frequency response at high penetration levels. Though the underlying mechanism has been relatively well understood, the accurate assessment and effective enhancement of the U.S. interconnections’ frequency response under extra-high PV penetration conditions remains an issue. In this paper, the industry-provided full-detail interconnection models were further validated by synchrophasor frequency measurements and realistically-projected PV geographic distribution information were used to develop extra-high PV penetration scenarios and dynamic models for the three main U.S. interconnections, including Eastern Interconnection (EI), Western Electricity Coordinating Council (WECC), and Electric Reliability Council of Texas (ERCOT). Up to 65% instantaneous PV and 15% wind penetration were simulated and the frequency response change trend of each U.S. interconnection due to the increasing PV penetration level were examined. Most importantly, the practical solutions to address the declining frequency response were discussed. This paper will provide valuable guidance for policy makers, utility operators and academic researchers not only in the U.S. but also other countries in the world.

Source Location Identification of Distribution-Level Electric Network Frequency Signals at Multiple Geographic Scales

The distribution-level electric network frequency (ENF) extracted from an electric power signal is a promising forensic tool for multimedia recording authentication. Local characteristics in ENF signals recorded in different locations act as environmental signatures, which can be potentially used as a fingerprint for location identification. In this paper, a reference database is established for distribution-level ENF using FNET/GridEye system. An ENF identification method that combines a wavelet-based signature extraction and feedforward artificial neural network-based machine learning is presented to identify the location of unsourced ENF signals without relying on the availability of concurrent signals. Experiments are performed to validate the effectiveness of the proposed method using ambient frequency measurements at multiple geographic scales. Identification accuracy is presented, and the factors that affect identification performance are discussed.

Measurement-based power system dynamic model reductions

Interconnected power systems experienced a significant increase in size and complexity. It is computationally burdensome to represent the entire system in detail to conduct power system analysis. Therefore, the model of the study system must be retained in detail while the external system can be reduced using system reduction techniques. This paper proposes a measurement-based dynamic equivalent in order to increase both model accuracy and simulation speed. The proposed method uses a set of measurements at the boundary nodes between the study area and external area for model parameter identification. Case studies demonstrate that the measurement-based technique can capture the main system behaviors accurately and improve computational efficiency.

Study of Wind and PV Frequency Control in U.S. Power Grids—EI and TI Case Studies

Renewable generations, such as variable-speed wind and photovoltaic (PV) power plants, have been expected to contribute to power systems’ frequency response. This paper studies wind and PV power plants’ frequency control in the U.S. Eastern Interconnection (EI) and Texas Interconnection (TI). Wide-area frequency measurement-validated EI and TI dynamic models and realistically projected renewable distribution information make these two case studies much more practical than previous studies based on only small test system models. A set of wind and PV power plant frequency controls, such as inertia control and governor control, are employed. This paper serves as a practical guidance on how to implement wind and PV frequency controls in a bulk power system with a high renewable penetration.