Pratama, R., Effendy, M., & Zulfatman, Z. (2018). Optimization of Maximum Power Point Tracking (MPPT) Using P&O-Fuzzy and IC-Fuzzy Algorithms on Photovoltaic. Kinetik, 3(2). doi:http://dx.doi.org/10.22219/kinetik.v3i2.200 Reveive April 28, 2017, Revise September 06, 2018, Accepted January, 02 2018 KINETIK, Vol. 3, No. 2, May 2018, Pp. 119-134 ISSN : 2503-2259 E-ISSN : 2503-2267 119 Optimization of Maximum Power Point Tracking (MPPT) Using P&O-Fuzzy and IC-Fuzzy Algorithms on Photovoltaic Rido Octa Pratama *1 , Machmud Effendy 2 , Zulfatman 3 1,2,3 Universitas Muhammadiyah Malang/Electrical Engineering roctapratama@gmail.com *1 , machmudefffendy@yahoo.com 2 , zulfatman.@umm.ac.id 3 Abstract Solar energy is energy which can be harnessed conveniently and free. However, its conversion result may not be easily obtained. Based on the previous research, solar power plant is a source of renewable energy, utilizing solar energy. Solar power plant converts solar energy into electricity using Photovoltaic (PV) or solar cells. Even though solar power plant is considered as better energy alternative, it presents problems and weaknesses. In this case, the problems are related to insufficient power generation with low power efficiency, high oscillation and very slow power tracking. Hence, in order to solve these problems, Maximum Power Point Tracking (MPPT) has been utilized. Combination method of P&O-fuzzy and IC-fuzzy is employed to its design. Moreover, combined algorithm may result better power from conventional algorithm due to appropriate performance of duty cycle according to system design, with efficiency result of 79%- 85.6%, tracking in searching output power of 0,0055s - 0,008s, low oscillation and maximum power generated by combined algorithm of 1028 watt. Keywords: Solar Cell, MPP, P&O-Fuzzy, IC-Fuzzy 1. Introduction Renewable energy has become a suitable solution to reduce the energy crisis and environmental issues in the world. Energy sources frequently used harness the existing natural resources such as water, sun, waves, wind and even geothermal. The utilization of renewable energy is also a reliable solution as a replacement of conventional energy sources which deplete their amount of reserves. One such renewable energy is photovoltaic [1]. While power generation using solar power is a great alternative to mitigate negative impacts on environmental issues, its application presents some problems. Those issues are exemplified by factors causing the electric power reduction generated by solar cells, such as solar intensity level and working temperature of the solar panels [2]. These problems may primarily persist if not utilizing Maximum Power Point Tracking (MPPT) control. MPPT is a control to maximize the performance of solar panels to obtain maximum power with good efficiency [3][4]. In the current MPPT, there are at least 19 different MPPT methods. Those methods are used as an algorithm to maximize the power attainment of solar cells. MPPT algorithms commonly used in the previous research are Perturb & Observe (P&O), Incremental Conductance (IC) and Fuzzy Logic Control (FLC) [5][6]. However, there are some existing weaknesses, such as not optimal power generation, frequently occurring oscillation around Maximum Power Point (MPP) area, slow tracking time to reach MPP value, unstable algorithm during climate changes, complexity in designing system algorithm and inaccuracy to achieve MPP value [7][8]. Therefore, we need a new technology to overcome the level of maximization of power output from solar cells; so that the power released can achieve maximum power with the resulting adequate efficiency. Afterwards, the method used in this study is a combination method between P&O-fuzzy and IC-fuzzy, which is expected to achieve maximum power with a good level of accuracy. Low oscillation is obtained with quicker duration power generation and easier design development [9][10]. 2. Research Method 2.1 PV Design The value of PV parameters used in this simulation is KC200GT-200W type. Broadly speaking, the PV modeling is obtained from equations which have been adapted to the characteristics of PV itself in general. Figure 1 presents PV’s schematic general circuit.