Dynamic Modeling and Renewable Integration Studies on the U.S. Power Grids

Wind and solar generation have gained a significant momentum in the last five years in the United States. According to the American Wind Energy Association, the installed wind power capacity has tripled from 25,410 MW in early 2009 to 74,472 MW as of the end of 2015. Meanwhile, solar photovoltaic (PV) is reported that its capacity has skyrocketed from 298 MW in 2009 to 7,260 MW in 2015 by the Solar Energy Industries Association. Despite the fact that wind and solar only make up 4.4% and 0.4% , respectively, of total electricity generation in 2014, the nation is right on its track to the Department of Energy (DOE)’s goal of 20% wind and 14% solar by year 2030. The future of renewable energy is aspiring. The rapid growth in renewable generation results in an urge to studying the reliability implication of renewable integration. For this purpose, two DOE projects were funded to the University of Tennessee, Knoxville, and the Oak Ridge National Laboratory. The first project, Grid Operational Issues and Analyses of the Eastern Interconnection (EI), is aimed at studying the dynamic stability impact of high wind penetration on the U.S. EI system in year 2030. The second project, Frequency Response Assessment and Improvement of Three Major North American Interconnections due to High Penetrations of Photovoltaic Generation, concentrates on the influence of high solar penetration on primary frequency response. This thesis documents the efforts of the above-mentioned two projects. Chapter 1 gives an introduction on power system dynamic modeling. Chapter 2 describes the process of dynamic models development. Chapter 3 discusses the adoption of synchro-phasor measurement for system-level dynamic model validation and the impact of turbine governor deadband on system dynamic response. Chapter 4 presents a stability impact study of high wind penetration on the U.S. Eastern Grid. Chapter 5 documents the modeling and simulation of the EI system under high solar penetration. Chapter 6 summaries two dynamic model reduction studies on the EI system. Conclusions, a summary of the major contribution of the Ph.D. work, and a discussion of possible future work are given in Chapter 7

Electromechanical Dynamics of High Photovoltaic Power Grids

This dissertation study focuses on the impact of high PV penetration on power grid electromechanical dynamics. Several major aspects of power grid electromechanical dynamics are studied under high PV penetration, including frequency response and control, inter-area oscillations, transient rotor angle stability and electromechanical wave propagation.To obtain dynamic models that can reasonably represent future power systems, Chapter One studies the co-optimization of generation and transmission with large-scale wind and solar. The stochastic nature of renewables is considered in the formulation of mixed-integer programming model. Chapter Two presents the development procedures of high PV model and investigates the impact of high PV penetration on frequency responses. Chapter Three studies the impact of PV penetration on inter-area oscillations of the U.S. Eastern Interconnection system. Chapter Four presents the impacts of high PV on other electromechanical dynamic issues, including transient rotor angle stability and electromechanical wave propagation. Chapter Five investigates the frequency response enhancement by conventional resources. Chapter Six explores system frequency response improvement through real power control of wind and PV. For improving situation awareness and frequency control, Chapter Seven studies disturbance location determination based on electromechanical wave propagation. In addition, a new method is developed to generate the electromechanical wave propagation speed map, which is useful to detect system inertia distribution change. Chapter Eight provides a review on power grid data architectures for monitoring and controlling power grids. Challenges and essential elements of data architecture are analyzed to identify various requirements for operating high-renewable power grids and a conceptual data architecture is proposed. Conclusions of this dissertation study are given in Chapter Nine

Data-Driven Situation Awareness for Power System Frequency Dynamics

As the penetration of renewable energy increases, system inertia decreases, causing changes in system frequency dynamics. The power industry desires situation awareness of power system frequency dynamics to ensure secure and economic operation and control. Moreover, FNET/Grideye has abundant measured data from power systems, making it possible to conduct data-driven situation awareness studies on power system frequency dynamics. This doctoral dissertation proposes several contributions: (a) Two accurate generator trip event MW estimation methods are proposed, in which one is based on long window RoCoF and another is based on multi-Beta values; (b) Two real-time system inertia estimation approaches are developed using ambient frequency fluctuation and pump turn-off events, along with techniques for improving RoCoF calculation in event-based inertia estimation; (c) An adaptive PV reserve estimation algorithm is established to provide PV reserve while saving energy for PV resources; (d) A practical load composition estimation tool is built for the industry to easily obtain essential load model parameters. Although conducting research using actual data from power systems for practical application is challenging and compilated, the proposed data-driven situation awareness methods in this doctoral dissertation solve practical problems and offer clear theoretical explanations for the industry. These methods address one of the key challenges for operating a high-renewable power grid and pave the way for the U.S. carbon-free power sector by 2035

Estimation of inherent governor dead-band and regulation using unscented Kalman filter

The inclusion of the governor droop and dead-band in dynamic models helps to reproduce the measured frequency response accurately and is a key aspect of model validation. Often, accurate and detailed turbine-governor information are not available for various units in an area control centre. The uncertainty in the droop also arise from the nonlinearity due to the governor valves. The droop and deadband are required to tune the secondary frequency bias factors, and to determine the primary frequency reserve. Earlier research on droop estimation did not adequately take into account the effect of dead-band and other nonlinearities. In this paper, unscented Kalman filter is used in conjunction with continuously available measurements to estimate the governor droop and the dead-band width. The effectiveness of the approach is demonstrated through simulation

Estimation of inherent governor dead-band and regulation using unscented Kalman filter

The inclusion of the governor droop and dead-band in dynamic models helps to reproduce the measured frequency response accurately and is a key aspect of model validation. Often, accurate and detailed turbine-governor information are not available for various units in an area control centre. The uncertainty in the droop also arise from the nonlinearity due to the governor valves. The droop and deadband are required to tune the secondary frequency bias factors, and to determine the primary frequency reserve. Earlier research on droop estimation did not adequately take into account the effect of dead-band and other nonlinearities. In this paper, unscented Kalman filter is used in conjunction with continuously available measurements to estimate the governor droop and the dead-band width. The effectiveness of the approach is demonstrated through simulation