Thesis
Three-phase distribution state estimation using smart meter data
Washington State University
Master of Science (MS), Washington State University
2016
Handle:
https://hdl.handle.net/2376/101536
Abstract
With ongoing smart grid activities, advancements in smart metering have been utilized for better situational awareness, and data analytics of active power distribution systems. Smart meters deployment for end-users constitutes major investment as part of the smart grid development for power distribution system. The two-way communications between 'power utility' and 'smart meters installed near end-user customers' assisted by meter data management systems helps to potentially realize numerous applications for enhanced monitoring and reliability of active distribution system. This thesis proposed a new solution for distribution system state estimation using smart meter data. As the first step, the equations for three-phase distribution state estimation is formulated based on the current injection method. For the second step, the classic weighted least squared algorithm is revised and applied for proposed distribution state estimation. For third step, a measurement uncertainty theory based bad data detection algorithm is proposed for detecting large errors in three-phase unbalanced distribution state estimation. The developed algorithm can optimize summation of normal measurement evaluation index to detect large errors. Developed techniques results in managing large errors in measurements while computing state estimation solution, simultaneously. The modified IEEE 13 bus system is used for testing and validation of the proposed algorithm, considering possible different location of measurements, time interval, and types of the measurements. Simulation results for number of different test cases indicate superior performance compared to existing methods in successfully detecting the large error bad data and accuracy of the state estimation in a distribution system.
Metrics
Details
- Title
- Three-phase distribution state estimation using smart meter data
- Creators
- Yu Guo
- Contributors
- Anurag K. Srivastave (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
- 99900525159001842
- Language
- English
- Resource Type
- Thesis