TY - GEN
T1 - Fuzzy Logic Based MPPT with Feedback Control for Photovoltaic Application
AU - Musafa, Akhmad
AU - Purnawan, Peby Wahyu
AU - Tri Yulianto, Alvin Setio
AU - Priyadi, Ardyono
AU - Pujiantara, Margo
AU - Purnomo, Mauridhi Hery
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/7/2
Y1 - 2018/7/2
N2 - This paper present design and implementation MPPT method using Fuzzy Logic Controller for photovoltaic system. Fuzzy MPPT in this work used to process of error and delta error that obtained from voltage sensor and current sensor on photovoltaic and voltage sensor and current sensor on DC-DC converter output as feedback signal. The error signal is obtained from the average of difference of the ratio of power changes to the voltage change from output of photovoltaic added the difference of the ratio of power change to the voltage change form output of DC-DC converter. The output of system is change of duty cycle (PWM signal) for switching DC-DC converter. Each input and output classified into seven membership function and defuzzification method used is Center of Largest Area. From the experimental result, for resistance load 7.14 ohms to 50 ohms the proposed MPPT system can increase the photovoltaic power by 11.73% at irradiation 475 W/m2 up to 532 W/m2. At irradiation 791 W/m2 to 816 W/m2, the proposed MPPT system can increase photovoltaic power by 10.85%, and at irradiation 1015 W/m2 to 1043 W/m2 can increase photovoltaic power of 3.71%. In the test for charging of 48V/12 Ah battery, when given a voltage reference of 52 volts and a current of 2 ampere the system is able to achieve steady state conditions within 13 seconds. For AC loads of lamps with power of 3 watts to 300 watts, the system has an average of efficiency 78.24%.
AB - This paper present design and implementation MPPT method using Fuzzy Logic Controller for photovoltaic system. Fuzzy MPPT in this work used to process of error and delta error that obtained from voltage sensor and current sensor on photovoltaic and voltage sensor and current sensor on DC-DC converter output as feedback signal. The error signal is obtained from the average of difference of the ratio of power changes to the voltage change from output of photovoltaic added the difference of the ratio of power change to the voltage change form output of DC-DC converter. The output of system is change of duty cycle (PWM signal) for switching DC-DC converter. Each input and output classified into seven membership function and defuzzification method used is Center of Largest Area. From the experimental result, for resistance load 7.14 ohms to 50 ohms the proposed MPPT system can increase the photovoltaic power by 11.73% at irradiation 475 W/m2 up to 532 W/m2. At irradiation 791 W/m2 to 816 W/m2, the proposed MPPT system can increase photovoltaic power by 10.85%, and at irradiation 1015 W/m2 to 1043 W/m2 can increase photovoltaic power of 3.71%. In the test for charging of 48V/12 Ah battery, when given a voltage reference of 52 volts and a current of 2 ampere the system is able to achieve steady state conditions within 13 seconds. For AC loads of lamps with power of 3 watts to 300 watts, the system has an average of efficiency 78.24%.
KW - MPPT
KW - feedback control
KW - fuzzy logic
KW - photovoltaic
UR - http://www.scopus.com/inward/record.url?scp=85066886148&partnerID=8YFLogxK
U2 - 10.1109/ISITIA.2018.8711272
DO - 10.1109/ISITIA.2018.8711272
M3 - Conference contribution
AN - SCOPUS:85066886148
T3 - Proceeding - 2018 International Seminar on Intelligent Technology and Its Application, ISITIA 2018
SP - 169
EP - 174
BT - Proceeding - 2018 International Seminar on Intelligent Technology and Its Application, ISITIA 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2018 International Seminar on Intelligent Technology and Its Application, ISITIA 2018
Y2 - 30 August 2018 through 31 August 2018
ER -
