Energy comparison of MPPT techniques for PV Systems under different atmospheric Conditions Hamidreza Khezri h.r.khezri2@gmail.com Mojtaba Farzaneh mojtaba.farzaneh@gmail.com Abstract— This article compares maximum power point tracking (MPPT), which plays an important role in Solar Photovoltaic (SPV). Fluctuation in electricity or power generation economically is not marketable and therefore electricity production must be kept at maximum power point (MPP) all the time. The cost of electricity from the PV array is more expensive, mainly due to the fact that its production is not very efficient than other electricity generation from non-renewable resources. Therefore, MPPT controllers are applied to improve the performance of PV systems with different requirements and conditions. The photovoltaic system is connected to a DC/DC boost converter to increase the output voltage. To extract the maximum power from a PV system, MPPT algorithms are implemented. In this project, we present a comparative simulation study of three MPPT techniques: Fuzzy Logic (FL), Incremental Conductance (InC), and Perturb & Observe (P&O) based MPPT controller under constant and variable environmental conditions. The simulation results show that FL based MPPT can track the MPP with faster response and good performance compared to the conventional (P&O) and (InC) algorithms by continuously adjusting the duty cycle of the DC/DC converter to track the maximum power of the solar cell. Thus, increasing the efficiency of the entire system. MATLAB/Simulink toolbox is used to develop and design the model of the PV solar system equipped with the proposed MPPT controller. Keywords— Solar Photo Voltaic (SPV), Maximum Power Point Tracking (MPPT), DC/DC boost converter, MATLAB/Simulink. I. INTRODUCTION As we know, energy is a vital role in our lives and the economy. Energy demand has increased in many industrial applications. Unfortunately, in recent years, greenhouse gas emissions, according to conventional energy production increases. This is a serious challenge to reducing carbon dioxide emissions and energy problems are overcome. The best solution is to use green energy sources such as sun and wind that produce free of pollution and sustainable energy in the future considered [1]. System Photovoltaic (PV) has a major research area for future energy needs. Thus, researchers have attracted much attention and seem to be one of the most stable sources of renewable energy. Solar energy is due to the lack of moving parts, security, lower maintenance, clean production and no sound [2] [3] [4]. However, two important factors affect the implementation of PV systems. These initial cost and low- efficiency solar panels because of unrealistic sun, cloud and shadow effects. Therefore, due to the I-V and P-V characteristics of PV panels, to increase efficiency we should always try to use the maximum power. In other words, the PV modules with the maximum voltage and current at the maximum power point indicate that the PV depends on the atmospheric conditions. PV systems have the following properties and technical challenges: 1. Depending on the irradiance and temperatures produce more power. 2. The large size of PV panels. 3. The cost of setting the PV system. 4. Difficulty in modelling the PV system behaviour. 5. The space it takes to put the PV panel. 6. The efficiency of the PV system. A boost converter is a DC/DC power converter that steps up the voltage from its input to its output [5]. The main purpose of this work is to compare three types of MPPT algorithm and find the best one to control the boost converter and gain maximum power of PV panels. In summary, in this paper, a comparative study of the majority of conventional controllers, perturbation and observation (P&O) and incremental conductance (InC) with fuzzy logic control (FLC), and analyzes them under various conditions such as radiation. The development of a FLC for MPPT is used to track the maximum power point of the PV modules to load and increase the system efficiency. The benefits of FL controller, in addition GSJ: Volume 7, Issue 8, August 2019 ISSN 2320-9186 1216 GSJ© 2019 www.globalscientificjournal.com