Dissertation
POWER SYSTEM DISTRIBUTED OSCILATION DETECTION BASED on SYNCHROPHASOR DATA
Doctor of Philosophy (PhD), Washington State University
01/2014
Handle:
https://hdl.handle.net/2376/5160
Abstract
Along with increasing demand for electricity, integration of renewable energy and deregulation of power market, power industry is facing unprecedented challenges nowadays. Within the last couple of decades, several serious blackouts have been taking place in United States. As an effective approach to prevent that, power system small signal stability monitoring has been drawing more interests and attentions from researchers.
With wide-spread implementation of Synchrophasors around the world in the last decade, power systems real-time online monitoring becomes much more feasible. Comparing with planning study analysis, real-time online monitoring would benefit control room operators immediately and directly. Among all online monitoring methods, Oscillation Modal Analysis (OMA), a modal identification method based on routine measurement data where the input is unmeasured ambient excitation, is a great tool to evaluate and monitor power system small signal stability. Indeed, high sampling Synchrophasor data around power system is fitted perfectly as inputs to OMA.
Existing methods in OMA for power systems are all based on centralized algorithms applying at control centers only; however, with rapid growing number of online Synchrophasors the computation burden at control centers is and will be continually exponentially expanded. The increasing computation time at control center compromises the real-time feature of online monitoring. The communication efforts between substation and control center will also be out of reach. Meanwhile, it is difficult or even impossible for centralized algorithms to detect some poorly damped local modes.
In order to avert previous shortcomings of centralized OMA methods and embrace the new changes in the power systems, two new distributed oscillation detection methods with two new decentralized structures are presented in this dissertation. Since the new schemes brought substations into the big oscillation detection picture, the proposed methods could achieve faster and more reliable results. Subsequently, this claim is tested and approved by test results of IEEE Two-area simulation test system and real power system historian synchrophasor data case studies.
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Details
- Title
- POWER SYSTEM DISTRIBUTED OSCILATION DETECTION BASED on SYNCHROPHASOR DATA
- Creators
- Jiawei Ning
- Contributors
- Mani Venkatasubramanian (Advisor)Anjan Bose (Committee Member)Anurag K Srivastava (Committee Member)
- Awarding Institution
- Washington State University
- Academic Unit
- Electrical Engineering and Computer Science, School of
- Theses and Dissertations
- Doctor of Philosophy (PhD), Washington State University
- Number of pages
- 84
- Identifiers
- 99900581736901842
- Language
- English
- Resource Type
- Dissertation