Smart Loading Management System for Hybrid Photovoltaic/Wind Power Supply

Abstract

Photovoltaic and wind turbine generation using environmentally friendly technology in the process of harvesting energy from the nature can be a solution to future electrical energy crises so that they become the most developed and reliable alternative. However, the conversion of solar/wind energy is highly dependent on the availability of sunlight and wind speed. Therefore, it is necessary to study the PV /wind loading which aims to increase and maintain the continuity of the electricity supply to the load. Load power management follows the availability of solar and wind energy in sunny, cloudy, rainy, or evening weather by considering the remaining usable battery voltage. Comparison of data is done to determine the system constraints with the ANFIS method. In testing the data with ANFIS performed with 3 MF (High, Medium, Low). From a total of 4003 data and an error of 26% was found, the training data was then compared with the test data. After testing the data comparison between the actual data and the training data that has been processed with ANFIS, it is obtained that there are more options for the maximum load that can be supplied by PV /wind generation. This has an impact on the performance of the hybrid PV /wind standalone which is more leverage on the loading side.