TY - JOUR
T1 - Enhancing Performance of Solar Photovoltaic Drip Irrigation System Through Binary Particle Swarm Optimization
AU - Suwito, Suwito
AU - Ashari, Mochamad
AU - Rivai, Muhammad
AU - Mustaghfirin, M. Anis
N1 - Publisher Copyright:
© 2022. International Journal of Intelligent Engineering and Systems. All Rights Reserved.
PY - 2022
Y1 - 2022
N2 - This paper presents a multisector drip irrigation system (DIS) powered by solar photovoltaic (PV). A binary particle swarm optimization (BPSO) method possibly determines irrigation in multisector, depending on the power availability of the solar PV. The power from solar PV in this study was optimized through maximum power point tracking (MPPT) using an incremental conductance (INC) method. A prototype was built using a PV emulator in 10 controlled irrigation sectors. Three operating modes applied include control of all sectors with BPSO, partly sectors with a combination of linear programming, and all sectors with bypassed without BPSO. Simulations and tests showed very similar results, indicating that the BPSO method provides an optimal and accurate irrigation system with 0.7 psi of an average irrigation operating pressure (IOP) error, 4.01 % of water volume error, and 96.55 % of the uniformity coefficient of water volume.
AB - This paper presents a multisector drip irrigation system (DIS) powered by solar photovoltaic (PV). A binary particle swarm optimization (BPSO) method possibly determines irrigation in multisector, depending on the power availability of the solar PV. The power from solar PV in this study was optimized through maximum power point tracking (MPPT) using an incremental conductance (INC) method. A prototype was built using a PV emulator in 10 controlled irrigation sectors. Three operating modes applied include control of all sectors with BPSO, partly sectors with a combination of linear programming, and all sectors with bypassed without BPSO. Simulations and tests showed very similar results, indicating that the BPSO method provides an optimal and accurate irrigation system with 0.7 psi of an average irrigation operating pressure (IOP) error, 4.01 % of water volume error, and 96.55 % of the uniformity coefficient of water volume.
KW - And microcontroller
KW - Binary particle swarm optimization
KW - Drip irrigation system
KW - Maximum power point tracking
KW - Photovoltaic
UR - http://www.scopus.com/inward/record.url?scp=85133014454&partnerID=8YFLogxK
U2 - 10.22266/ijies2022.0831.34
DO - 10.22266/ijies2022.0831.34
M3 - Article
AN - SCOPUS:85133014454
SN - 2185-310X
VL - 15
SP - 382
EP - 393
JO - International Journal of Intelligent Engineering and Systems
JF - International Journal of Intelligent Engineering and Systems
IS - 4
ER -