Members: Audrey Baricko, Travis Wardlow, Kelly Brennan*
Primary Advisors: Dr. Anthony Deese and Dr. Jennifer Wang
State estimation is a data processing scheme to find unknown variables, or states based on measurements and topology. In a power system, the states are voltage magnitudes and voltage angles. Knowledge of the states will permit informed decisions and adjustments to be made to increase a power system’s performance. Currently, state estimation is performed from a centralized location on a PC. The main problem associated with this process is that the time to execute calculations increases exponentially as the number of variables increases. In addition, as power systems evolve to include distributed power generation; micro-grid and smart grid technology will be required. State estimation is an integral part of such technology.
In this project a distributed state estimation design will be developed that partitions a large system into smaller systems. This approach will minimize the complexity, and therefore, time that it takes to perform the calculations. Implementing the distributed state estimator on a microcontroller will additionally minimize the cost. Phasor Measurement Units will be utilized to relay vital system information to the state estimator using TCP/IP protocols. The Phasor Measurement Unit will measure voltage magnitude and include GPS technology to measure time delays, so that voltage angle can be found. To create a reference point for the voltage angle calculations, a synchronous motor and sensors will be used. The distributed estimation will not create an exact solution; however, the goal of this project is to maximize accuracy while minimizing cost, and to measure the feasibility of distributed estimation as an alternative to the current methods of state estimation.
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* Non E/CE majors