Maximum Power Point Tracking Design Based on Fuzzy Logic Algorithm Under Uncertain Weather Condition

Abstract

Electricity is one of the main sources of energy that is very important in everyday life, both for household needs, government agencies, and industry. To strengthen the implementation sustainable development goal by reducing the use of fossil fuel, the utilization of solar energy has great potential, though the efficiency of solar panels or solar energy technology is still relatively low, especially in Indonesia. Located in tropical region, the solar panel module receives solar irradiation that varies due to changes in weather or local environmental conditions, partial shading will occur, making the solar panels partially covered by shadows. This situation will result in a decrease in the output power of solar panels To overcome this issue, a battery is used to store the generated energy. To maximize the potential, the battery needs to be charged optimally which need a control algorithm to provide energy gathered from the solar panel, most of the time. Therefore, a maximum power point tracking (MPPT) is necessary to be associated with an algorithm to optimally control the performance of the solar energy harvesting scheme. In this study, both Mamdani and Sugeno Fuzzy Logic Algorithm are used in the MPPT with a buck converter at a solar panel with a battery. Buck converter is chosen to give safety charging margin to the battery since the converter's output voltage is lower than the input voltage. As for the fuzzy logic algorithm, Mamdani's Fuzzy Logic has the advantage of producing more accurate decision results than Sugeno's type. While, Sugeno's Fuzzy Logic has the advantage of using simple mathematical calculations in its design. In addition, a buck converter was also used to match the voltage generated by the solar panel to match the battery specifications. The system design and testing are carried out using Matlab R2018b Simulink. From the simulation, the Mamdani Fuzzy Logic-based MPPT has the same maximum power point tracking computation time as Sugeno's Fuzzy Logic. In the partial shading test conditions, MPPT based on Fuzzy Logic has a higher efficiency value of 94.50% when compared to MPPT without control which is only 89.56%. Under various conditions of irradiation and temperature, MPPT based on Fuzzy Logic has a higher efficiency value of 94.88% than MPPT without control which is only efficiency of 91.53%.