TY - GEN
T1 - A Comparative Study of Maximum Power Point Tracking Algorithms for Wind Energy Systems in Giligenting Island
AU - Soedibyo,
AU - Adila, Ahmad Firyal
AU - Anam, Sjamsjul
AU - Ashari, Mochamad
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/8
Y1 - 2019/8
N2 - Wind energy systems have become a major commodity in the use of renewable energy resources, but its implementation requires great technical challenges in power extraction. Giligenting Island, Madura, East Java, is a prospective area for wind energy development. An algorithm applied to obtain optimal power from wind power generation. This paper presents a performance evaluation of the methods that can be applied as the MPPT (Maximum Power Point Tracking) algorithms. P&O (Perturbation and Observation), IC (Incremental Conductance), and PSO (Particle Swarm Optimization) are studied and discussed as the MPPT techniques in this research. All three methods are implemented on systems that have the same characteristics, they are compared to the simulation results. At the base wind turbine speed of 12 m/s, the P&O method obtained MPPT power of 295.82 W with settling time at 1.02 s. The IC method obtained MPPT power of 297.08 W with settling time at 1 s. Then, The PSO method achieved an MPPT power of 297.45 W with time settling at 0.88 s. According to the simulation results, the PSO is the algorithm that provided the best performance among all MPPT algorithms studied. Beside good response to wind speed variations, PSO also has a simple structure and easy to implement.
AB - Wind energy systems have become a major commodity in the use of renewable energy resources, but its implementation requires great technical challenges in power extraction. Giligenting Island, Madura, East Java, is a prospective area for wind energy development. An algorithm applied to obtain optimal power from wind power generation. This paper presents a performance evaluation of the methods that can be applied as the MPPT (Maximum Power Point Tracking) algorithms. P&O (Perturbation and Observation), IC (Incremental Conductance), and PSO (Particle Swarm Optimization) are studied and discussed as the MPPT techniques in this research. All three methods are implemented on systems that have the same characteristics, they are compared to the simulation results. At the base wind turbine speed of 12 m/s, the P&O method obtained MPPT power of 295.82 W with settling time at 1.02 s. The IC method obtained MPPT power of 297.08 W with settling time at 1 s. Then, The PSO method achieved an MPPT power of 297.45 W with time settling at 0.88 s. According to the simulation results, the PSO is the algorithm that provided the best performance among all MPPT algorithms studied. Beside good response to wind speed variations, PSO also has a simple structure and easy to implement.
KW - Incremental Conductance
KW - MPPT (Maximum Power Point Tracking) algorithms
KW - Particle Swarm Optimization
KW - Perturbation and Observation
KW - wind energy
UR - http://www.scopus.com/inward/record.url?scp=85078465428&partnerID=8YFLogxK
U2 - 10.1109/ISITIA.2019.8937136
DO - 10.1109/ISITIA.2019.8937136
M3 - Conference contribution
AN - SCOPUS:85078465428
T3 - Proceedings - 2019 International Seminar on Intelligent Technology and Its Application, ISITIA 2019
SP - 114
EP - 119
BT - Proceedings - 2019 International Seminar on Intelligent Technology and Its Application, ISITIA 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2019 International Seminar on Intelligent Technology and Its Application, ISITIA 2019
Y2 - 28 August 2019 through 29 August 2019
ER -
