Power Forecasting from Solar Panels Using Artificial Neural Network in UTHM Parit Raja

This paper presents a step-by-step procedure for the simulation of photovoltaic modules with numerical values, using MALTAB/Simulink software. The proposed model is developed based on mathematical PV module, which solar cell employing one-diode equivalent circuit. output current and power characteristics curves highly depend some climatic factors such as radiation temperature, are obtained by selected module. collected data used in developing Artificial Neural Network (ANN) model. Multilayer Perceptron (MLP) Radial Basis Function (RBF) techniques to forecast outputs PV. Various types activation function will be applied Linear, Logistic Sigmoid, Hyperbolic Tangent Sigmoid Gaussian. results show that best technique produce minimal root mean square error system.