Development of a Converter-Based Testing Platform and Battery Energy Storage System (BESS) Emulator for Microgrid Controller Function Evaluation

The microgrid has attracted increasing research attention in the last two decades. Due to the development of renewable energy resources and power electronics technologies, the future microgrid will trend to be smarter and more complicated. The microgrid controller performs a critical role in the microgrid operation, which will also become more and more sophisticated to support the future microgrid. Before final field deployment and test, the evaluation and testing of the controller is an indispensable step in the controller development, which requires a proper testing platform. However, existing simulation-based platforms have issues with potential numerical oscillation and may require huge computation resources for complex microgrid controllers. Meanwhile, field test-based controller evaluation is limited to the test conditions. Existing digital simulation-based platforms and field test-based platforms have limitations for microgrid controller testing. To provide a practical and flexible controller evaluation, a converter-based microgrid hardware testbed is designed and implemented considering the actual microgrid architecture and topology information. Compared with the digital simulation-based platforms, the developed microgrid testing platform can provide a more practical testing environment. Compared to the direct field test, the developed platform is more flexible to emulate different microgrids. As one of the key components, a converter-based battery energy storage system (BESS) emulator is proposed to complete the developed testing platform based on the testing requirements of microgrid controller functions. Meanwhile, the microgrid controller testing under different microgrid conditions is also considered. Two controllers for the microgrid with dynamic boundaries are tested to demonstrate the capability of the developed platform as well as the BESS emulator. Different testing cases are designed and tested to evaluate the controller performance under different microgrid conditions

Virtual Synchronous Generator Operation of Full Converter Wind Turbine ‒ Control and Testing in a Hardware Based Emulation Platform

Wind is one of the most promising renewable energy forms that can be harvested to into the electrical power system. The installation has been rising worldwide in the past and will continue to steadily increase. The high penetration of wind energy has bought about a number of difficulties to the power system operation due to its stochastic nature, lack of exhibited inertia, and differing responses to the traditional energy sources in grid disturbances. Various grid support functions are then proposed to resolve the issues. One solution is to allow the renewable energy sources to behave like a traditional synchronous generator in the system, as a virtual synchronous generator (VSG). On the other hand, testing the control of the future power grid with high penetration renewable often relies on digital simulation or hardware-based experiments. But they either suffer from fidelity and numerical stability issues, or are bulky and inflexible. A power electronics based power system emulation platform is built in the University of Tennessee. This Hardware Testbed (HTB) allows testing of both system level and component level controls, with a good balance between the fidelity of the hardware-based testing platform, and the coverage of the digital simulation.This dissertation proposal investigates the VSG operation of the full converter wind turbine (FCWT), focusing on its control and testing in the HTB. Specifically, a FCWT emulator was developed using a single converter to include its physical model and control strategies. The existing grid support functions are also included to demonstrate their feasibility.The comprehensive VSG controls are then proposed for a FCWT with short term energy storage. The dynamic response of the FCWT can be comparable to the traditional generation during grid disturbance. The control can also allow the FCWT to be dispatched by the system operator, and even operate stand-alone without other grid sources.To study the system response under faults, a short circuit fault emulator was developed in the HTB platform. Four basic types of the short circuit faults with various fault impedance can be emulated using the emulator. The power system transient stability in terms of critical clearing time can be measured using the developed fault emulator

Wide-Area Measurement-Driven Approaches for Power System Modeling and Analytics

This dissertation presents wide-area measurement-driven approaches for power system modeling and analytics. Accurate power system dynamic models are the very basis of power system analysis, control, and operation. Meanwhile, phasor measurement data provide first-hand knowledge of power system dynamic behaviors. The idea of building out innovative applications with synchrophasor data is promising. Taking advantage of the real-time wide-area measurements, one of phasor measurements’ novel applications is to develop a synchrophasor-based auto-regressive with exogenous inputs (ARX) model that can be updated online to estimate or predict system dynamic responses. Furthermore, since auto-regressive models are in a big family, the ARX model can be modified as other models for various purposes. A multi-input multi-output (MIMO) auto-regressive moving average with exogenous inputs (ARMAX) model is introduced to identify a low-order transfer function model of power systems for adaptive and coordinated damping control. With the increasing availability of wide-area measurements and the rapid development of system identification techniques, it is possible to identify an online measurement-based transfer function model that can be used to tune the oscillation damping controller. A demonstration on hardware testbed may illustrate the effectiveness of the proposed adaptive and coordinated damping controller. In fact, measurement-driven approaches for power system modeling and analytics are also attractive to the power industry since a huge number of monitoring devices are deployed in substations and power plants. However, most current systems for collecting and monitoring data are isolated, thereby obstructing the integration of the various data into a holistic model. To improve the capability of utilizing big data and leverage wide-area measurement-driven approaches in the power industry, this dissertation also describes a comprehensive solution through building out an enterprise-level data platform based on the PI system to support data-driven applications and analytics. One of the applications is to identify transmission-line parameters using PMU data. The identification can obtain more accurate parameters than the current parameters in PSS®E and EMS after verifying the calculation results in EMS state estimation. In addition, based on temperature information from online asset monitoring, the impact of temperature change can be observed by the variance of transmission-line resistance