Browsing by Author "Bi, Tianshu"
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- Improved Dynamical Analysis Tools for DFIG Wind Farms via Traditional and Koopman LinearizationsMitchell-Colgan, Elliott (Virginia Tech, 2019-09-27)The electric power system is designed to economically and reliably transmit electricity to homes, industry, and businesses. The economic impact of the electric grid was demonstrated by the 2003 blackout's visible impact in the graph of the yearly gross domestic product of the Unites States. However, because the number of customers is so large and economies of scale are leveraged to keep electricity prices low, utilities are strongly interconnected. Performing comprehensive engineering analyses to ensure reliable operation is still impossible. Instead, heuristics and safety factors are incorporated into planning processes to continually meet demand in a way that complies with Federal regulations. As evidenced by the infrequency of blackouts in the United States, the sophisticated planning processes have up to date been relatively successful. However, the power system is constantly changing. Electrical generators based on renewable energies are a beneficial addition to the grid, but these and other technological changes like high-voltage power electronic converters also come with their own challenges. These systems as currently employed tend to have a different impact on the reliability of operation than traditional fossil fuel based generators. As the system changes, so do the engineering analyses required to ensure reliable operation. In particular, the wind energy conversion systems (WECS) negatively impact the response of the grid to disturbances in certain ways due to inherent challenges harnessing the wind as an energy sources. These negative impacts (and the advent of powerful personal computing) require an increase in the sophistication of power system models. Thus, there are competing challenges: the scale of the power system necessitates computationally efficient modeling, but the complexity of analysis required to maintain reliable operation is also increasing. The primary aim of this study is to develop models and methods for more detailed yet computationally manageable simulation. To this aim, higher order linearizations and the properties of linear systems (graph theory and linear algebra) are exploited. More specifically, this document contains three studies. In the short term planning and situational awareness context, a method is proposed to quickly check credible outages of important grid equipment. This methodology enables the inspection of a wider breadth of system conditions to ameliorate the negative impacts of the unpredictability of the wind. A linear model in the traditional sense is also developed to model any arbitrary number of wind turbines in a wind farm. This enables industry players to study the impacts wind turbine interaction on the dynamic stability of the grid in response to small disturbances. Finally, a wind farm is modeled as a large matrix to model even nonlinear behavior of wind farms. This helps industry players analyze the impact of large disturbances on the grid.
- Phasor measurement units, WAMS, and their applications in protection and control of power systemsPhadke, Arun G.; Bi, Tianshu (2018-07-05)The paper provides a short history of the phasor measurement unit (PMU) concept. The origin of PMU is traced to the work on developing computer based distance relay using symmetrical component theory. PMUs evolved from a portion of this relay architecture. The need for synchronization using global positioning system (GPS) is discussed, and the wide area measurement system (WAMS) utilizing PMU signals is described. A number of applications of this technology are discussed, and an account of WAMS activities in many countries around the world are provided.
- Roles of Dynamic State Estimation in Power System Modeling, Monitoring and OperationZhao, Junbo; Netto, Marcos; Huang, Zhenyu; Yu, Samson Shenglong; Gomez-Exposito, Antonio; Wang, Shaobu; Kamwa, Innocent; Akhlaghi, Shahrokh; Mili, Lamine M.; Terzija, Vladimir; Meliopoulos, A. P. Sakis; Pal, Bikash; Singh, Abhinav Kumar; Abur, Ali; Bi, Tianshu; Rouhani, Alireza (IEEE, 2020-09-30)Power system dynamic state estimation (DSE) remains an active research area. This is driven by the absence of accurate models, the increasing availability of fast-sampled, time-synchronized measurements, and the advances in the capability, scalability, and affordability of computing and communications. This paper discusses the advantages of DSE as compared to static state estimation, and the implementation differences between the two, including the measurement configuration, modeling framework and support software features. The important roles of DSE are discussed from modeling, monitoring and operation aspects for today's synchronous machine dominated systems and the future power electronics-interfaced generation systems. Several examples are presented to demonstrate the benefits of DSE on enhancing the operational robustness and resilience of 21st century power system through time critical applications. Future research directions are identified and discussed, paving the way for developing the next generation of energy management systems and novel system monitoring, control and protection tools to achieve better reliability and resiliency.