Indiana University-Purdue University Indianapolis (IUPUI) / The electrical disturbances in the power system have threatened the stability of the system. In the first step, it is necessary to detect these electrical disturbances or events. In the next step, a proper control should apply to the system to decrease the consequences of the disturbances.
One-shot control is one of the effective methods for stabilizing the events. In this method, a proper amount of loads are increased or decreased to the electrical system. Determining the amounts of loads, and the location for shedding is crucial. Moreover, some control combinations are more effective for some events and less effective for some others. Therefore, this project is completed in two different sections. First, finding the effective control combinations, second, finding an algorithm for applying different control combinations to different contingencies in real-time.
To find effective control combinations, sensitivity analysis is employed to locate the most effective loads in the system. Then to find the control combination commands, gradient descent, and PSO algorithm are used in this project. In the next step, a pattern recognition method is used to apply the appropriate control combination for every event. The decision tree is selected as the pattern recognition method.
The three most effective control combinations found by sensitivity analysis and the PSO method are used in the remainder of this study. A decision tree is trained for each of the three control combinations, and their outputs are combined into an algorithm for selecting the best control in real-time. Finally, the algorithm is evaluated using a test set of contingencies. The final results reveal a 30\% improvement in comparison to the previous studies.
| Identifer | oai:union.ndltd.org:IUPUI/oai:scholarworks.iupui.edu:1805/19944 |
| Date | 08 1900 |
| Creators | Iranmanesh, Shahrzad |
| Contributors | Steven, Rovnyak, King, Brian, dos Santos, Euzeli Cipriano |
| Source Sets | Indiana University-Purdue University Indianapolis |
| Language | English |
| Detected Language | English |
| Type | Thesis |
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