TY - GEN
T1 - Optimization of Horizontal Axis Tidal Turbines Farming Configuration Using Particle Swarm Optimization (PSO) Algorithm
AU - Mubarok, Muhammad Asroril
AU - Arini, Nu Rhahida
AU - Satrio, Dendy
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Turbines installed in farming have slightly different characteristics. Mainly the problem is when several tidal turbines are placed side by side at the location of the tidal current flow. Therefore, is it necessary to predict energy at specific marine locations or to optimize the arrangement of turbines. The farm layout is precisely arranged to obtain the best position. One of the stages of optimizing turbines is the effective placement of turbine configuration using the Particle Swarm optimization (PSO) algorithm. This method is suitable for solving turbine positioning problems. This study aims to optimize position optimization to obtain the maximum power and minimum cost per power of the turbine using the PSO algorithm. The optimization of 2D position in three different scenarios has a substantial impact on the spacing between turbines and effects of objective function. The results of case 3 have a higher objective function value than cases 1 and 2, with an objective function value of 2.330 for five turbines and 1.415 for ten. The result shows turbine arrangement, the three cases show the influence of the current direction from various directions showing positions that are more spread out and pointing in identical directions but do not significantly affect the power generated. Speed has a significant effect on the power produced by the turbine. Variations in direction cause the position of the turbine to spread, while at an identical speed in one direction, the turbine's position is directed in that direction. The PSO method can produce optimal solutions at a cost per product in complex environments with varying directions and speeds in actual circumstances.
AB - Turbines installed in farming have slightly different characteristics. Mainly the problem is when several tidal turbines are placed side by side at the location of the tidal current flow. Therefore, is it necessary to predict energy at specific marine locations or to optimize the arrangement of turbines. The farm layout is precisely arranged to obtain the best position. One of the stages of optimizing turbines is the effective placement of turbine configuration using the Particle Swarm optimization (PSO) algorithm. This method is suitable for solving turbine positioning problems. This study aims to optimize position optimization to obtain the maximum power and minimum cost per power of the turbine using the PSO algorithm. The optimization of 2D position in three different scenarios has a substantial impact on the spacing between turbines and effects of objective function. The results of case 3 have a higher objective function value than cases 1 and 2, with an objective function value of 2.330 for five turbines and 1.415 for ten. The result shows turbine arrangement, the three cases show the influence of the current direction from various directions showing positions that are more spread out and pointing in identical directions but do not significantly affect the power generated. Speed has a significant effect on the power produced by the turbine. Variations in direction cause the position of the turbine to spread, while at an identical speed in one direction, the turbine's position is directed in that direction. The PSO method can produce optimal solutions at a cost per product in complex environments with varying directions and speeds in actual circumstances.
KW - Horizontal Axis Tidal Turbine
KW - Ocean Renewable Energy
KW - PSO
KW - Tidal Farm
KW - optimization
UR - http://www.scopus.com/inward/record.url?scp=85173615525&partnerID=8YFLogxK
U2 - 10.1109/IES59143.2023.10242450
DO - 10.1109/IES59143.2023.10242450
M3 - Conference contribution
AN - SCOPUS:85173615525
T3 - IES 2023 - International Electronics Symposium: Unlocking the Potential of Immersive Technology to Live a Better Life, Proceeding
SP - 19
EP - 25
BT - IES 2023 - International Electronics Symposium
A2 - Yunanto, Andhik Ampuh
A2 - Ramadhani, Afifah Dwi
A2 - Prayogi, Yanuar Risah
A2 - Putra, Putu Agus Mahadi
A2 - Ruswiansari, Maretha
A2 - Ridwan, Mohamad
A2 - Gamar, Farida
A2 - Rahmawati, Weny Mistarika
A2 - Rusli, Rusli Muhammad
A2 - Humaira, Fitrah Maharani
A2 - Adila, Ahmad Firyal
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 25th International Electronics Symposium, IES 2023
Y2 - 8 August 2023 through 10 August 2023
ER -