In recent years, with the energy shortage, the use of renewable energy is inevitable. With CO2 the most important greenhouse gas causing global warming as well as the increase of population, renewable energy is one way to save energy and reduce carbon emissions. The traditional capacity investment for serving the load in distribution systems usually considered the addition of new substations or expansion of the existing substation and associated new feeder requirement. Nowadays, there are a lots of distributed generations (DG¡¦s) to be chosen. Factors of the choice taken into account will include lower pollution, higher efficiency, higher return rate for construction of distributed power generation systems.
This thesis assumes that the distributed generation can be invested for long-term power plant planning. The planning of DG would be investigated from the perspectives of the independent investors. The modified Particle Swarm Optimization is proposed to determine the optimal sizing and sit of DG¡¦s addition in distribution systems with the constrains of CO2 limitation and addition of distributed generation to maximize profits. This thesis deals with discrete programming problem of optimal power flow, which includes continuous and discrete types of variables. The continuous variables are the generating unit real power output and the bus voltage magnitudes, the discrete variables are the shunt capacitor banks and sit problems. The Miaoli-Houlong system of Taiwan power will be used in this thesis for the verification of the feasibility of the proposed method.
Identifer | oai:union.ndltd.org:NSYSU/oai:NSYSU:etd-0627111-201856 |
Date | 27 June 2011 |
Creators | Lin, Chang-ming |
Contributors | Ta-Peng Tsao, Whei-min Lin, none |
Publisher | NSYSU |
Source Sets | NSYSU Electronic Thesis and Dissertation Archive |
Language | Cholon |
Detected Language | English |
Type | text |
Format | application/pdf |
Source | http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0627111-201856 |
Rights | campus_withheld, Copyright information available at source archive |
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