Universiti Teknologi Malaysia Institutional Repository

Short term load forecasting using data mining technique

Wan Abdul Razak, Intan Azmira and Majid, Md. Shah and Abd. Rahman, Hasimah and Hassan, Mohammad Yusri (2008) Short term load forecasting using data mining technique. In: Proceedings of 2008 2nd IEEE International Conference on Power and Energy (PECon 2008) , 2008, Johor Bahru, Johor.

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Official URL: http://dx.doi.org/10.1109/PECON.2008.4762460


Accurate load and price forecasting are become very essential in power system planning. This will increase the efficiency of electricity generation and distribution while maintaining sufficient security of operation. This paper proposes method for Short Term Load Forecasting using data mining technique. The data provided by utility of Malaysia were analyzed to see its behavior or load pattern in a day during weekday and weekend in Peninsular Malaysia. By considering day-type in a week, five model of SARIMA (Time Series approach) have been created using Minitab. The forecasting is held based on the similar repeating trend of patterns from historical load data. The half hourly load data for six weeks had been plotted according to day-type to forecast the load demand for a day ahead. The MAPEs (Mean Absolute Percentage Error) obtained were ranging from 1.07% to 3.26%. Hence this modeling had improved the accuracy of forecasting rather than using only one model for all day in a week.

Item Type:Conference or Workshop Item (Paper)
Uncontrolled Keywords:short term load forecasting, power system operation, data mining, time series, ARIMA model
Divisions:Electrical Engineering
ID Code:16010
Deposited By: Siti Khairiyah Nordin
Deposited On:13 Oct 2011 14:54
Last Modified:12 Jun 2017 04:19

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