MPPE for Solar PV Using ANN Based on Open Circuit Voltage and Short Circuit Current

In this current millennial era, the demand for energy resources will be even higher, along with the increasing population in the world. The type of renewable energy that is widely adopted is a photovoltaic cell or solar PV. In its application, the energy or power that can be produced by solar PV is very volatile, depending on many factors. On the other hand, the demand of the load side also changes significantly so that the acquisition of solar PV often cannot adjust to the energy load needs. Therefore in this paper, a system is created that can predict the power that can be produced by a solar PV in a particular region and operated at a certain light intensity in real-time. This prediction system is called the Maximum Power Point Estimation (MPPE). Various methods can do the power estimation on the panel, and the method used in this paper is Artificial Neural Network (ANN) approach. To be able to do power estimation, this system uses two main parameters obtained directly from solar PV, which are open-circuit voltage (Voc) and short circuit current (Isc). The parameters obtained will change if the intensity of sunlight also varies. Therefore, by using the Voc and Isc parameters as an input data of ANN algorithm, this system can be succeeded predict the maximum power that can be generated by a solar PV following the intensity of sunlight received in real-time, with a maximum error estimation of 0.02845% and average of 0.01049%.