Lu, Michelle (2017) Swarm Evolutionary Programming Method for Optimal Under-Frequency Load Shedding Scheme. PhD thesis, UNIMAS.
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Abstract
This thesis investigated the coupling effects of power system frequency and voltage and reflects this critical relationship in the analytic System Frequency Response (SFR)-UFLS model in the form of load-generation imbalance. The analytic SFR-UFLS model was used to compute the UFLS performance indicators from derived closed-form expressions of the load frequency response. This thesis proposed a new method of incorporating swarm features into the optimization algorithm of Classical Evolutionary Programming (CEP) to derive optimal settings for the UFLS scheme. The proposed method called the Swarm Evolutionary Programming (SEP) which is also a variant of CEP, was tested on the Western System Coordinating Council (WSCC) nine-bus system. Simulation results have shown that SEP was able to produce an optimal load-shedding scheme with superior performance. There are no nonlinear constraints violations and the minimum transient frequency deviation is reduced by 0.295Hz and 0.075Hz compared to traditional trial-and-error and CEP methods. There are also no over-frequency problems in terms of steady-state frequency deviation and the total quantum of load shedding is reduced by 0.1154p.u as compared to the CEP method.
| Item Type: | Thesis (PhD) |
|---|---|
| Additional Information: | Thesis (Ph.D.) -- Universiti Malaysia Sarawak, 2017. |
| Uncontrolled Keywords: | Under-Frequency Load Shedding, System Frequency Response, Classical Evolutionary Programming, Swarm Evolutionary Programming, unimas, university, universiti, Borneo, Malaysia, Sarawak, Kuching, Samarahan, ipta, education, Postgraduate, research, Universiti Malaysia Sarawak. |
| Subjects: | T Technology > T Technology (General) T Technology > TK Electrical engineering. Electronics Nuclear engineering |
| Divisions: | Academic Faculties, Institutes and Centres > Faculty of Engineering Faculties, Institutes, Centres > Faculty of Engineering |
| Depositing User: | Gani |
| Date Deposited: | 31 Jul 2018 01:52 |
| Last Modified: | 27 Jun 2023 07:04 |
| URI: | http://ir.unimas.my/id/eprint/21023 |
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