Thesis
Power Plant Model Validation Using Synchrophasor Data from Multiple Events
Washington State University
Master of Science (MS), Washington State University
2017
Handle:
https://hdl.handle.net/2376/104604
Abstract
Accurate parameter estimation of generator model is necessary for power system planning to ensure precise analysis of power stability. Parameter estimation using online measurements is trending in real-time power system operations due to its nonintrusiveness and cost efficiency. Model parameter can be estimated by adjusting model parameters referring to local event data. Estimation method using online measurements has been proven to be accurate in capturing dynamic model behavior of generators. Practically, real-time event data at generator node are available for study. Many digital protective relays can measure the three-phase instantaneous voltage and current signals and compute voltage and power phasor accordingly. Since generator models at one node only interacts with models at other nodes through the network, empirical dynamic model with local input-output information at one node is sufficient to represent its model behavior in a large-scale network. In this study, a framework is proposed as generic standard process for selecting suitable events to estimate generator model parameters at local node. The proposed framework serves as guideline specifying event measurement effective for estimating specific model parameters.This offline optimization framework is cost-efficient due to less negative impact on power systems. Three sets of generator model estimation are demonstrated to validate the proposed framework. Further discussion is provided on some popular algorithms and their performance on the model settings applied throughout this study. On the other hand, nature of the specified algorithm impacts on optimization result. Generally, evolution algorithms(EAs) demonstrate robustness in optimization. This study provides demonstration cases pointing out the challenges faced by certain algorithms, aiming to shed some light on algorithm selection.
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Details
- Title
- Power Plant Model Validation Using Synchrophasor Data from Multiple Events
- Creators
- Pikkin Jim Lau
- Contributors
- Mani Vaithianathan Venkatasubramanian (Degree Supervisor)
- Awarding Institution
- Washington State University
- Academic Unit
- Electrical Engineering and Computer Science, School of
- Theses and Dissertations
- Master of Science (MS), Washington State University
- Publisher
- Washington State University; [Pullman, Washington] :
- Identifiers
- 99900525106001842
- Language
- English
- Resource Type
- Thesis