TY - GEN
T1 - Analyze and optimization of genetic algorithm implemented on maximum power point tracking technique for PV system
AU - Megantoro, Prisma
AU - Wijaya, Fransisco Danang
AU - Firmansyah, Eka
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/7/1
Y1 - 2017/7/1
N2 - In photovoltaic system, Solar Charge Controller (SCC) device has vital role to keep the performance to get system efficiency higher. It is done by tracking the maximum power point on solar cell array where power transfer is on its maximum condition. This level is on V-I curve where curve characteristic depends on temperature and sun irradiation level happen on the moment. There are a lot of algorithms have been developed to increase the efficiency to this process, it is included to artificial intelligence based algorithm. One of them is genetic algorithm as heuristic method developed to imitate the natural selection process. The implementation of this algorithm is conducted for tracking process of maximum power point. This research used modelling to compare this tracking technique to tracking process which used analytical method. Furthermore, correlation analysis was done to parameters used to output parameter. Research results showed that the implementation of genetic algorithm to maximum power point had excellently on tracking accuracy parameter and tracking time. While correlation test showed that parameter of individual number and generation number effected significantly to the increasing of tracking accuracy and tracking time.
AB - In photovoltaic system, Solar Charge Controller (SCC) device has vital role to keep the performance to get system efficiency higher. It is done by tracking the maximum power point on solar cell array where power transfer is on its maximum condition. This level is on V-I curve where curve characteristic depends on temperature and sun irradiation level happen on the moment. There are a lot of algorithms have been developed to increase the efficiency to this process, it is included to artificial intelligence based algorithm. One of them is genetic algorithm as heuristic method developed to imitate the natural selection process. The implementation of this algorithm is conducted for tracking process of maximum power point. This research used modelling to compare this tracking technique to tracking process which used analytical method. Furthermore, correlation analysis was done to parameters used to output parameter. Research results showed that the implementation of genetic algorithm to maximum power point had excellently on tracking accuracy parameter and tracking time. While correlation test showed that parameter of individual number and generation number effected significantly to the increasing of tracking accuracy and tracking time.
KW - Genetic algorithm
KW - Maximum power point tracking
KW - Photovoltaic
UR - http://www.scopus.com/inward/record.url?scp=85046008668&partnerID=8YFLogxK
U2 - 10.1109/ISEMANTIC.2017.8251847
DO - 10.1109/ISEMANTIC.2017.8251847
M3 - Conference contribution
AN - SCOPUS:85046008668
T3 - Proceedings - 2017 International Seminar on Application for Technology of Information and Communication: Empowering Technology for a Better Human Life, iSemantic 2017
SP - 79
EP - 84
BT - Proceedings - 2017 International Seminar on Application for Technology of Information and Communication
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2017 International Seminar on Application for Technology of Information and Communication, iSemantic 2017
Y2 - 7 October 2017 through 8 October 2017
ER -