Dealing with front-end white noise on differentiated measurements such as frequency and ROCOF in power systems

This paper describes the way that white noise (including quantised input section sampling) imparts errors onto frequency and rate-of-change-of-frequency (ROCOF) measurements. The main paper focus concerns the use of filtered heterodyned (i.e. Fourier) analyses for single-phase and 3-phase systems, and the filtered Clarke transform for 3-phase systems. The rules and equations governing the effect of white noise on frequency and ROCOF are formulated for these techniques, explaining the subtle effects of aliasing, splitting signals and noise into their positive and negative frequency components, and the correlation or de-correlation of noise. It is shown that - as expected - for 3-phase AC measurements, averaging 3 single-phase Fourier measurements produces the same performance against noise as using a method based on Clarke’s transform, if identical filtering is used. Furthermore, by understanding the theory behind the frequency and ROCOF measurement processes, it is shown that to achieve the lowest RMS errors, in the presence of front-end white noise (alone, ignoring other dynamic signal and power quality aspects), a filter which provides ~40 dB/decade attenuation (i.e. a 2-boxcar cascade) is recommended for a frequency measurement, but a filter which rolls off at ~60 dB/decade (i.e. a 3-boxcar cascade) is recommended for a ROCOF measurement

The Impact of Large-scale Dynamic Load Modeling on the U.S. Eastern Interconnection

The aim of this thesis is to introduce widespread dynamic load models to the United States Eastern Interconnection 2030 power grid model to help improve its accuracy and capabilities. Currently, all loads in the system are represented by static load models that are unable to capture load phenomenon associated with induction motors. Chapter 1 will provide a general introduction to load modeling by discussing popular static and dynamic load models available. This chapter will also introduce the simulation test case used in Chapter 2 to Chapter 4. In Chapter 2, the complex load model parameters are developed and applied to 28,500 loads in the Eastern Interconnection model and the impact to frequency response is discussed. Buses with large differences in frequency nadir when static or dynamic load models are applied to the system and a bus with a representative response are presented for reference. Snapshots from a movie illustrate the frequency map distribution for the Eastern Interconnection. Chapter 3 is a sensitivity study of the complex load model for certain parameters. The induction motor, constant power, discharge lighting, and static load components of the complex load model are studied. The study metrics are the frequency nadir, settling frequency, and rate of change of frequency for the system average response and a single bus. Chapter 4 validates the developed model for real events recorded by the FNET/Grideye system. The accuracy of the dynamic load model is compared to the current static load model. Chapter 5 discusses the process to develop load models for a utility in the Eastern Interconnection using a bottom-up approach. The developed models are studied for several cases and validated

Studies of Uncertainties in Smart Grid: Wind Power Generation and Wide-Area Communication

This research work investigates the uncertainties in Smart Grid, with special focus on the uncertain wind power generation in wind energy conversion systems (WECSs) and the uncertain wide-area communication in wide-area measurement systems (WAMSs). For the uncertain wind power generation in WECSs, a new wind speed modeling method and an improved WECS control method are proposed, respectively. The modeling method considers the spatial and temporal distributions of wind speed disturbances and deploys a box uncertain set in wind speed models, which is more realistic for practicing engineers. The control method takes maximum power point tracking, wind speed forecasting, and wind turbine dynamics into account, and achieves a balance between power output maximization and operating cost minimization to further improve the overall efficiency of wind power generation. Specifically, through the proposed modeling and control methods, the wind power control problem is developed as a min-max optimal problem and efficiently solved with semi-definite programming. For the uncertain communication delay and communication loss (i.e. data loss) in WAMSs, the corresponding solutions are presented. First, the real-world communication delay is measured and analyzed, and the bounded modeling method for the communication delay is proposed for widearea applications and further applied for system-area and substation-area protection applications, respectively. The proposed bounded modeling method is expected to be an important tool in the planning, design, and operation of time-critical wide-area applications. Second, the real synchronization signal loss and synchrophasor data loss events are measured and analyzed. For the synchronization signal loss, the potential reasons and solutions are explored. For the synchrophasor data loss, a set of estimation methods are presented, including substitution, interpolation, and forecasting. The estimation methods aim to improve the accuracy and availability of WAMSs, and mitigate the effect of communication failure and data loss on wide-area applications

Wide-Area Measurement-Based Applications for Power System Monitoring and Dynamic Modeling

Due to the increasingly complex behavior exhibited by large-scale power systems with more uncertain renewables introduced to the grid, wide-area measurement system (WAMS) has been utilized to complement the traditional supervisory control and data acquisition (SCADA) system to improve operators’ situational awareness. By providing wide-area GPS-time-synchronized measurements of grid status at high time-resolution, it is able to reveal power system dynamics which cannot be captured before and has become an essential tool to deal with current and future power grid challenges. According to the time requirements of different power system applications, the applications can be roughly divided into online applications (e.g., data visualization, fast disturbance and oscillation detection, and system response prediction and reduction) and offline applications (e.g., measurement-driven dynamic modeling and validation, post-event analysis, and statistical analysis of historical data). In this dissertation, various wide-area measurement-based applications are presented. Firstly a pioneering WAMS deployed at the distribution level, the frequency monitoring network (FNET/GridEye) is introduced. For conventional large-scale power grid dynamic simulation, two major challenges are 1) accuracy of detailed dynamic models, and 2) computation burden for online dynamic assessment. To overcome the restrictions of the traditional approach, a measurement-based system response prediction tool using a Multivariate AutoRegressive (MAR) model is developed. It is followed by a measurement-based power system dynamic reduction tool using an autoregressive model vi to represent the external system. In addition, phasor measurement unit (PMU) data are employed to perform the generator dynamic model validation study. It utilizes both simulation data and measurement data to explore the potentials and limitations of the proposed approach. As an innovative application of using wide-area power system measurement, digital recordings could be authenticated by comparing the extracted frequency and phase angle from recordings with power system measurement database. It includes four research studies, i.e., oscillator error removal, ENF phenomenology, tampering detection, and frequency localization. Finally, several preliminary data analytics studies including inertia estimation and analysis, fault-induced delayed voltage recovery (FIDVR) detection, and statistical analysis of oscillation database, are presented