CAREER: The Science of Measurement-based Stability Assessment and Model Validation for Microgrids

点击翻译按钮获取中文摘要

Measurement-based stability assessment and model validation tools have enjoyed considerable success in bulk power systems (BPS). Due to the unique challenges that microgrids pose, such as unbalanced loading, short line lengths, and high prevalence of inverter-based generation (IBG), such tools cannot be directly applied. Instead, novel and creative approaches must be considered. Microgrid tools must employ multirate signal processing that incorporate data from multiple domains. Additionally, the analysis tools will need to consider stability metrics beyond the modal damping used in the BPS. Finally, synchronized point-on-wave (SPOW) data will be required to capture both the fast inverter dynamics along with all three phases. This work has the potential to dramatically increase the reliability and resiliency of microgrids by providing stakeholders with real-time indicators of stability along with regular model validation and tuning. This will enable more rapid and reliable designs of microgrids, which has the potential to (1) accelerate the paradigm shift from central to distributed generation, (2) reduce community dependence on large corporate- or government-owned energy resources, (3) foster increased use of renewable energy, and (4) enable a new level of rural electrification. The SPOW-based model validation researched here can also be applied to the BPS, where greater confidence in a proposed installation of IBG will lead to increased penetration of renewables, battery storage, and EV charging stations. Outreach activities include visits to local K-12 classrooms where students will be invited to creatively present the history of electric power. At the collegiate level, this project will redesign and modernize the power curriculum at Union College, including a cross-disciplinary course that merges power engineering and music theory that will culminate in a public concert of sonified power grid data. Finally, this project will support the training of a postdoctoral researcher that will be well-prepared to continue these endeavors upon the conclusion of their term. The objective of the project is to research and define the modeling and simulation techniques, the system ID algorithms, and system measurements or functions of measurements that are necessary to enable measurement-based power grid stability assessment and model validation in microgrids. The first task towards achieving this objective is to build a repository of microgrid models. This will involve existing benchmark systems that may be modified as well as new models created specifically for this project. A library of simulation cases will be built that will cover several types of microgrid stability. A real-time digital simulator with hardware-in-loop (HIL) capabilities will be used to simulate the models with the option of including hardware inverter controllers and point-on-wave measurement devices. The second task is to identify which system outputs are necessary for measurement-based stability assessment and model validation in a microgrid. This will need to move beyond synchrophasors, and may include mechanical measurements and SPOW data. This will involve the prototyping of an SPOW measurement device. The third task will research system identification and detection and estimation algorithms for use in measurement-based stability assessment. It is expected that a suite of algorithms will be selected, each specializing in the analysis of a particular stability type. The final task will investigate the use of inverter-based probing signals to facilitate model validation using SPOW data without having to wait for a system event. Successful completion of all tasks will result in a comprehensive system for achieving measurement-based stability assessment and model validation in microgrids.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.