Short-term load forecasting using AR and ARIMA box Jenkins model / Romi Ehendra Abdul Aziz
This paper presents an overview research on the short term load forecasting (STLF) in power system field. The method used in this approach was based on autoregressive (AR) Box Jenkins model. AR was mathematical model in solving iteration problem. The AR model was selected based on the behavior of th...
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| Format: | Thesis |
| Language: | English |
| Published: |
2008
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| Online Access: | https://ir.uitm.edu.my/id/eprint/67130/2/67130.pdf https://ir.uitm.edu.my/id/eprint/67130/ |
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| Summary: | This paper presents an overview research on the short term load forecasting (STLF) in power system field. The method used in this approach was based on autoregressive (AR) Box Jenkins model. AR was mathematical model in solving iteration problem. The AR model was selected based on the behavior of the sample autocorrelation (SAC) and sample partial autocorrelation (SPAC). Furthermore the adequacy of the AR model was determined by Ljung Box test. The (AR) Box Jenkins model then is compared with the ARIMA Box Jenkins model to determine the performance of both models in assessment of STLF. The main purpose was to study the important of load forecasting. Whereby from the load forecasting analysis we can estimate on how many generation plants that have to turn on in certain period time, and switching. |
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