AI SearchElectrical load forecasting in Nepal : application of time series and simulation methods
Call Number: AIT Thesis no. ET-90-14 Material type:
TextSeries: Asian Institute of Technology. Thesis ; no. ET-90-14Publication details: Bangkok : Asian Institute of Technology, 1990Description: 120 pSubject(s): Online resources: Dissertation note: Thesis (M.Eng.) - Asian Institute of Technology, 1990 Summary: This study deals with the problem of short term and long term peak load forecasting in Nepal. The stochastic time series Autoregressive Integrated Moving average (ARIMA) method has been used to forecast load in the hourly, daily, weekly and the monthly time horizons. In the paper, the bivariate transfer function model with temperature as an explanatory variable is used to forecast the hourly peak demand of a small area. A comparison of the transfer function model and the ARIMA model (to forecast hourly demand) found that transfer function model performed better than the ARIMA model. The long term simulation type of forecasting model called Model for Analysis of the Energy Demand (MAED) is used to forecast the annual pealed load and the system load curves. The analysis and simulation of t h e system load curves under different hypothetical conditions suggested that load management strategies could possibly implemented (in Nepal) to reduce the peak load in the intermediate term. The case study was carried out for the integrated electric system of Nepal Electricity Authority.
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Asian Institute of Technology Library AIT Publications | AIT Thesis no. ET-90-14 (Browse shelf(Opens below)) | 1 | Available | 30050003105532 | |||||||||||||
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Asian Institute of Technology Library AIT Publications | AIT Thesis no. ET-90-14 (Browse shelf(Opens below)) | 2 | Available | 30050003655346 | |||||||||||||
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Asian Institute of Technology Library Archives | AIT Thesis no. ET-90-14 (Browse shelf(Opens below)) | Available | 30050120344311 |
A thesis submitted in partial fulfillment of the requirements of Master of Engineering, School of Engineering and Technology
Thesis (M.Eng.) - Asian Institute of Technology, 1990
This study deals with the problem of short term and long term peak load forecasting in Nepal. The stochastic time series Autoregressive Integrated Moving average (ARIMA) method has been used to forecast load in the hourly, daily, weekly and the monthly time horizons. In the paper, the bivariate transfer function model with temperature as an explanatory variable is used to forecast the hourly peak demand of a small area. A comparison of the transfer function model and the ARIMA model (to forecast hourly demand) found that transfer function model performed better than the ARIMA model. The long term simulation type of forecasting model called Model for Analysis of the Energy Demand (MAED) is used to forecast the annual pealed load and the system load curves. The analysis and simulation of t h e system load curves under different hypothetical conditions suggested that load management strategies could possibly implemented (in Nepal) to reduce the peak load in the intermediate term. The case study was carried out for the integrated electric system of Nepal Electricity Authority.
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