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DC Field | Value | Language |
---|---|---|
dc.contributor.author | Tatcha Sudtasan | en_US |
dc.contributor.author | Komsan Suriya | en_US |
dc.date.accessioned | 2018-09-04T09:48:38Z | - |
dc.date.available | 2018-09-04T09:48:38Z | - |
dc.date.issued | 2014-01-01 | en_US |
dc.identifier.issn | 21945357 | en_US |
dc.identifier.other | 2-s2.0-84897825575 | en_US |
dc.identifier.other | 10.1007/978-3-319-03395-2_35 | en_US |
dc.identifier.uri | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84897825575&origin=inward | en_US |
dc.identifier.uri | http://cmuir.cmu.ac.th/jspui/handle/6653943832/53394 | - |
dc.description.abstract | This study uses maximum entropy method to find an optimal combination of energy sources for electricity generation in Thailand. It sets three targets including unit cost, risk and pollution. In the optimization process, it forms three constraints according to these three targets. It solves the system following the guideline of Golan, Judge and Miller (1996). It analyses six scenarios of the targets. For the major results, it finds that hydropower, nuclear, wind and solar energy are major sources of electricity generation. The country cannot avoid adopting nuclear energy for its electricity generation in order to meet all the three targets that are optimal for its electricity generation and economic development. © Springer International Publishing Switzerland 2014. | en_US |
dc.subject | Computer Science | en_US |
dc.subject | Engineering | en_US |
dc.title | Optimal combination of energy sources for electricity generation in Thailand with lessons from Japan using maximum entropy | en_US |
dc.type | Book Series | en_US |
article.title.sourcetitle | Advances in Intelligent Systems and Computing | en_US |
article.volume | 251 | en_US |
article.stream.affiliations | Chiang Mai University | en_US |
Appears in Collections: | CMUL: Journal Articles |
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