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Utilization of renewable energy from solar panel systems is increasingly being applied, but until now its utilization has not been maximized. The movement of the sun caused by rotation of the earth and cloudy condition should be taken into account to maximize the electrical energy in solar panels. In this study, a concept to calculate the movement of a two-axis sun tracker is proposed by using a combination of two controller methods, i.e. Proportional Integral Derivative (PID) and Fuzzy logic known as Fuzzy-PID (F-PID). To follow the movement of the sun, the LDR sensor is used as an input to light as well as output used to drive 2 units servo for x-axis and y-axis. Sun tracker that is used is based on tetrahedron geometry and uses three Light Dependent Resistor (LDR) sensors as input. Input and output components are connected to the Atmega 328P by using a combination of Fuzzy logic and PID programs (F-PID). Fuzzy logic programming is first performed on the Matlab application using Fuzzy Inference System (FIS), then converted into an Arduino-based programming language. The sun tracker movement and the voltage received by the solar panel will be stored into the SD card using a data logging module. Adjusting the sun tracker movement using the combined Fuzzy logic and PID method intends to maximize the electrical energy received by the solar panel. The results showed that the F-PID method obtained the maximum voltage of 5.3 V, a maximum current of 0.11 A, and a maximum power of 0.61 W.

Solar modules have current and voltage characteristics that are non-linear, so efforts must always be made to work at the maximum power point so that no energy is wasted. The characteristics of the solar module will change depending on the level of radiation and temperature which causes the output power of the solar module to fluctuate and become unstable. To reduce oscillations in the output power of the solar module, the Fuzzy Logic Control (FLC) method used using the boost converter. Several studies have been done to maximize the output power of solar panels, one of which is by using namely by using Maximum Power Point Tracking (MPPT). This study aims to obtain the maximum power point in a set of solar modules arranged in series and parallel through the performance of the FLC method. In tracking the maximum power point during normal operation, the fuzzy method works together with a boost converter. Fuzzy-based MPPT was tested on a solar module under several radiation and temperature conditions using Matlab / Simulink software. The Fuzzy design method shows better results compared to other methods. The results obtained show the advantages of the FLC method in terms settling time, power loss, and oscillation at the point of the operating system.

Solar panels are an essential part of a system of electrical source devices that receives light energy to be processed into electrical energy with direct current (DC) output. The main problem in the use of solar panels is that the production of power in solar panels is not constant due to the temperature and solar radiation changes. This non-constant power causes the solar panel output power to fluctuate and become unstable. This output power will be used in processing using the MPPT Perturb and Observe (PNO) method to obtain the maximum solar panel receiving point. This PNO method uses two input parameters and can be applied to all types of solar panels. This study aims to reduce the oscillation of the output power of MPPT using electronic power simulations on a three-level boost converter by combining PNO and Fuzzy MPPT methods. The Fuzzy method in this study uses the Mamdani inference method, which uses two inputs and one output. The boost converter was tested using a simulation on several conditions of sunlight received by solar panels. The simulation results show that the power output from the MPPT PNO and Fuzzy methods can reduce oscillation more optimally, 78.57%.