Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor | Faculty of Engineering | en_US |
| dc.creator | Wang, Zhen | - |
| dc.identifier.uri | https://theses.lib.polyu.edu.hk/handle/200/7315 | - |
| dc.language | English | en_US |
| dc.publisher | Hong Kong Polytechnic University | - |
| dc.rights | All rights reserved | en_US |
| dc.title | Optimal reactive power dispatch | en_US |
| dcterms.abstract | Electric power industry is currently undergoing revolution in both technology and industry restructuring. As a consequence, the optimization problems have become vital. This paper presents differential evolution based optimal reactive power dispatch for real power loss minimization in power system. The objective of this project is to minimize the real power loss subjected to limits on generator real and reactive power outputs, bus voltages, transformer taps and shunt power compensated capacitors. It will introduce what Differential Evolution is and represent the mathematical expression of optimal reactive power dispatch at first. The problem is formulated as a mixed integer nonlinear optimization problem. The algorithm is tested on IEEE30 system to find for the optimal control variables. The result shows differential evolution algorithm is effective. All the data processing and model simulations will be conducted on MATLAB and its toolboxes (Mat power & DE math). | en_US |
| dcterms.extent | ix, 62 leaves : ill. ; 30 cm. | en_US |
| dcterms.isPartOf | PolyU Electronic Theses | en_US |
| dcterms.issued | 2012 | en_US |
| dcterms.educationalLevel | All Master | en_US |
| dcterms.educationalLevel | M.Sc. | en_US |
| dcterms.LCSH | Electric power systems -- Control. | en_US |
| dcterms.LCSH | Mathematical optimization. | en_US |
| dcterms.LCSH | Hong Kong Polytechnic University -- Dissertations | en_US |
| dcterms.accessRights | restricted access | en_US |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| b26493184.pdf | For All Users (off-campus access for PolyU Staff & Students only) | 1.8 MB | Adobe PDF | View/Open |
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