AI SearchElectricity demand forecast for the Kingdom of Thailand
Call Number: AIT Thesis no.ET-85-13 Material type:
TextSeries: Asian Institute of Technology. Thesis ; no. ET-85-13Publication details: Bangkok : Asian Institute of Technology, 1985Description: 94 pSubject(s): Online resources: Dissertation note: Thesis (M.Eng.) - Asian Institute of Technology, 1985 Summary: This thesis presents different methods of model formulation and application for the long run electricity demand forecast of the Kingdom of Thailand. This is one of a few studies concerning regional analysis to investigate and characterize the local demand pattern of electricity. It looks into the sectoral demand forecast of a region and of an integrated system. The profound concept of dynamic response was formulated by using a variable adjustment method to verify the dynamic effect of each socioeconomic variable and these are compared to the results of log-linear demand models. The demand was also estimated by using various cases and the results obtained were compared using the reference scenario of each case.
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22-AIT Thesis (Replacement)
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Asian Institute of Technology Library AIT Publications | AIT Thesis no.ET-85-13 (Browse shelf(Opens below)) | 3 | Available | 30050120679070 | |||||||||||||
40-Archives
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Asian Institute of Technology Library Archives | AIT Thesis no.ET-85-13 (Browse shelf(Opens below)) | Available | 30050120353072 |
A thesis submitted in partial fulfillment of requirements for the degree of Master of Engineering, School of Environment, Resources and Development
Thesis (M.Eng.) - Asian Institute of Technology, 1985
This thesis presents different methods of model formulation and application for the long run electricity demand forecast of the Kingdom of Thailand. This is one of a few studies concerning regional analysis to investigate and characterize the local demand pattern of electricity. It looks into the sectoral demand forecast of a region and of an integrated system. The profound concept of dynamic response was formulated by using a variable adjustment method to verify the dynamic effect of each socioeconomic variable and these are compared to the results of log-linear demand models. The demand was also estimated by using various cases and the results obtained were compared using the reference scenario of each case.
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