According to the proposed definition and classification of power system stability addressed by IEEE and CIGRE Task Force, voltage stability refers to the stability of maintaining the steady voltage magnitudes at all buses in a power system when the system is subjected to a disturbance from a given operating condition (OC). Cascading outage due to voltage collapse is a probable consequence during insecure voltage situations. In this regard, fast responding and reliable voltage security assessment (VSA) is effective and indispensable for system to survive in conceivable contingencies. This paper aims at establishing an online systematic framework for voltage security assessment with high-speed data streams from synchrophasors and phasor data concentrators (PDCs). Periodically updated decision trees (DTs) have been applied in different subjects of security assessments in power systems. However, with a training data set of operating conditions that grows rapidly, re-training and restructuring a decision tree becomes a time-consuming process. Hoeffding-tree-based method constructs a learner that is capable of memory management to process streaming data without retaining the complete data set for training purposes in real-time and guarantees the accuracy of learner. The proposed approach of voltage security assessment based on Very Fast Decision Tree (VFDT) system is tested and evaluated by the IEEE 118-bus standard system. / Master of Science / Voltage security is one of the most critical issues in the power systems operation. Given an operating condition (OC), Voltage Security Assessment (VSA) provides a tool to access whether the system is capable to withstand disturbances if there is one or more than one elements is not functioning appropriately on the power grid. Traditional methods of VSA require the knowledge of network topologies and the computational contingency analysis of various circumstances. With trained models, decision-tree-based VSA is able to assess the voltage security status by collectible measurements among the system in a real-time manner. The system topology may alter over and over by system operators in order to meet the needs of heavy load demand and power quality requirements. The proposed approach based on Very Fast Decision Tree (VFDT) system is capable of updating trained decision-tree models regarding to changes of system topology. Therefore, the updated decision-tree models is able to handle different system topology and to provide accurate security assessment of current OC again.
| Identifer | oai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/78805 |
| Date | 05 September 2017 |
| Creators | Nie, Zhijie |
| Contributors | Electrical and Computer Engineering, Centeno, Virgilio A., Kekatos, Vasileios, De La Ree, Jaime |
| Publisher | Virginia Tech |
| Source Sets | Virginia Tech Theses and Dissertation |
| Detected Language | English |
| Type | Thesis |
| Format | ETD, application/pdf |
| Rights | In Copyright, http://rightsstatements.org/vocab/InC/1.0/ |
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