Prediction of Rooftop Photovoltaic Power Generation Using Artificial Neural Network

被引：0

作者：

Wee, Yun Nee ^{[1
]}

Nor, Ahmad Fateh Mohamad ^{[1
]}

机构：

[1] Univ Tun Hussein Onn Malaysia UTHM, Fac Elect & Elect Engn, Green & Sustainable Energy Focus Grp GSEnergy, Batu Pahat, Johor, Malaysia

来源：

2020 18TH IEEE STUDENT CONFERENCE ON RESEARCH AND DEVELOPMENT (SCORED) | 2020年

关键词：

photovoltaic; solar electricity; renewable energy; ANN; MODEL;

D O I：

暂无

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

Photovoltaic (PV) system is known as one of the most popular renewable energy types in generating electricity power. However, one of the drawbacks of PV system is that the performance of PV panel output is incompatible and affected due to changing climate condition. Hence, it is important to predict the optimal power output of PV system. This study will cover the implementation of PV system at the rooftop of Faculty of Electrical and Electronic Engineering, Universiti Tun Hussein Onn Malaysia. Then, the optimal PV output power on the rooftop NI ill be predicted using calculation method and Artificial Neural Network (ANN). The results have shown that ANN has the ability to predict the PV output close to the calculation method.

引用

页码：346 / 351

页数：6

共 20 条

[1]

Accuweather, BAT PAH WEATH

[2]

Assahout S., 2018, International Journal of Power Electronics and Drive System (IJPEDS), V9, P1823, DOI [10.11591/ijpeds.v9.i4.pp1823-1833, DOI 10.11591/IJPEDS.V9.I4.PP1823-1833]

[3] Hardware implementation of an artificial neural network model to predict the energy production of a photovoltaic system [J].