Open AccessPeningkatan Efisiensi Photovolata dengan Menggunakan Pelacakan Daya Titik Maksimum Berdasarkan
Author(s) -
Machmud Effendy,
Khusnul Hidayat,
Wahyu Dianto Pramana
Publication year - 2018
Publication title -
jeee-u (journal of electrical and electronic engineering-umsida)/jte-u (jurnal teknik elektro universitas muhammadiyah sidoarjo)
Language(s) - English
Resource type - Journals
eISSN - 2540-8658
pISSN - 2460-9250
DOI - 10.21070/jeee-u.v2i2.1703
Subject(s) - maximum power point tracking , photovoltaic system , particle swarm optimization , maximum power principle , control theory (sociology) , boost converter , matlab , computer science , ripple , power (physics) , irradiance , voltage , physics , electrical engineering , engineering , inverter , algorithm , control (management) , quantum mechanics , artificial intelligence , operating system
Photovoltaic (PV) is a device which is capable to converts solar irradiance into Direct Current (DC) electricity energy. To increase the power result of PV, it needs a method to track the Maximum Power Point(MPP) which is usually called Maximum power Point Tracking(MPPT). So that, the power result increased with low cost. The purpose of this research is to conduct MPPT modeling by Particle Swarm Optimization (PSO). The proposed method is implemented in DC to DC converter. This research used SEPIC converter. The purpose of using SEPIC converter is in order the output of current and voltage have smallest ripple. The modelling system is conducted by using MATLAB 2016b software to find out performance of PSO and SEPIC converter. The evaluation of PSO and SEPIC converter performance has been done. The simulation result shows that the proposed system has been working very well. The PSO has good accurateness in tracking and capable to to track the power produced by PV with velocity around ±4,2 seconds when in conditions STC, ±9,2 seconds when in conditions partial shading, despite a fluctuating irradiance change. While in SEPIC converter is able to reach efficiency of ≥ 80%.