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Hourly photovoltaics power output prediction for Malaysia using support vector regression

Baharin, Kyairul Azmi and Abdul Rahman, Hasimah and Hassan, Mohammad Yusri and Chin, Kim Gan (2015) Hourly photovoltaics power output prediction for Malaysia using support vector regression. In: 2015 9th International Power Engineering and Optimization Conference, 18-19 Mar, 2015, Melaka, Malaysia.

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Official URL: https://eventegg.com/peoco-2015/

Abstract

Reliable solar energy forecasting enables grid operators to manage the grid better as PV penetration level increases. This research explores the use of support vector regression to forecast hourly power output from a grid-connected PV system in Malaysia. Data is obtained from a grid-connected PV system that is equipped with a weather monitoring station. Three parameters are used as input to the forecast model; global irradiance, tilted irradiance and ambient temperature. Results were compared against a persistence model. The SVR model manages to forecast hourly power production with satisfactory accuracy.

Item Type:Conference or Workshop Item (Paper)
Uncontrolled Keywords:solar energy forecasting, photovoltaics
Subjects:T Technology > TJ Mechanical engineering and machinery
Divisions:Electrical Engineering
ID Code:61458
Deposited By: Widya Wahid
Deposited On:25 Apr 2017 03:49
Last Modified:07 Aug 2017 00:36

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