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Journal : JURNAL INTEGRASI

DESAIN DAN IMPLEMENTASI INTERLEAVED BOOST CONVERTER UNTUK POWER FACTOR CORRECTION MENGGUNAKAN PENGENDALI LOGIKA FUZZY Mentari Putri Jati; Era Purwanto; Bambang Sumantri; Sutedjo Sutedjo; Dimas Okky Anggriawan
JURNAL INTEGRASI Vol 12 No 1 (2020): Jurnal Integrasi - April 2020
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (939.784 KB) | DOI: 10.30871/ji.v12i1.1430

Abstract

In recent years there is an increasing demand for closely regulated dc power supply. Most of the power electronic converters in these power supplies used full wave rectifier. Bulky filter capacitor in rectifier can effect non-sinusoidal input current waveform (distorted). The difference in voltage and current waveform affected the power factor system. Interleaved Boost Converter (IBC) as Power Factor Correction (PFC) with a fuzzy logic controller to be added in the system to achieved near to unity power factor. IBC operated in Discontinuous Conduction Mode (DCM). Power factor near to unity can be achieved while rectifier supplied resistive load, the waveform of load current through back to input source have the same form with the input voltage. Simulation and hardware implementation is used by varying loads. The experimental results with a variable load value of IBC as PFC can improve the power factor system from 0.67 to 0.93.
EFFICIENT MAXIMUM POWER POINT ESTIMATION MONITORING OF PHOTOVOLTAIC USING FEED FORWARD NEURAL NETWORK Hasnira Hasnira; Novie Ayub Windarko; Anang Tjahjono; Mochammad Ari Bagus Nugroho; Mentari Putri Jati
JURNAL INTEGRASI Vol 12 No 2 (2020): Jurnal Integrasi - Oktober 2020
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/ji.v12i2.2161

Abstract

The development of the utilization of solar panels in the future will continue to increase. One characteristic form of solar panels is the I-V curve which can be used to analyze the amount of solar panel output power. By knowing the I-V curve, we can get Maximum Power Point Estimation (MPPE) value that can be supported by solar panels. Information about the estimated value of the maximum solar panel power is an important part in determining the loading capacity, while maintaining the life of the equipment used. Feed Forward Neural Network with Back Propagation Algorithm (FFBP) has proven to be able to provide MPPE value information on solar panel output. The input values ​​in ANN are the voltage and current of the solar panel, while the output of ANN is in the form of an estimated power value. MPPE simulation results obtained an average error of 0.04 points between actual power (MPP) and estimated power (MPPE).