TY - GEN
T1 - Dynamic Optimal Power Flow with PV and BMS Integration in the Power Grid Using TFWO Method
AU - Widarsono, Kukuh
AU - Soeprijanto, Adi
AU - Wibowo, Rony Seto
AU - Aryani, Ni Ketut
AU - Oktaviani, Berliandra
AU - Nur, Mohammad
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - This research proposes a new optimization method, 'Turbulent Flow of Water-Based Optimization (TWFO),' for Dynamic Optimal Power Flow (DOPF) solutions. The objective function in this research is the minimum cost of thermal generation. During operation, optimization must be adapted to network constraints (bus voltage, generator ramp rate, and network capacity). This research will use the IEEE 30 bus to integrate with PV and BMS. The total power produced by PV and BMS will reduce the power that must be generated by the thermal generator to serve the installed load, which will then be optimized using the dynamic optimal power flow (DOPF) method. System IEEE 30 bus with three cases of OPF (base case, PV integration case, and PV and BMS integration case) was used to validate the performance of TWFO. Apart from that, checks were also carried out with the comparison algorithm (GA). From these three cases, it is proven that TWFO has better performance than GA.
AB - This research proposes a new optimization method, 'Turbulent Flow of Water-Based Optimization (TWFO),' for Dynamic Optimal Power Flow (DOPF) solutions. The objective function in this research is the minimum cost of thermal generation. During operation, optimization must be adapted to network constraints (bus voltage, generator ramp rate, and network capacity). This research will use the IEEE 30 bus to integrate with PV and BMS. The total power produced by PV and BMS will reduce the power that must be generated by the thermal generator to serve the installed load, which will then be optimized using the dynamic optimal power flow (DOPF) method. System IEEE 30 bus with three cases of OPF (base case, PV integration case, and PV and BMS integration case) was used to validate the performance of TWFO. Apart from that, checks were also carried out with the comparison algorithm (GA). From these three cases, it is proven that TWFO has better performance than GA.
KW - Batteries Management Systems (BMS)
KW - GA
KW - TFWO
KW - dynamic optimal power flow (DOPF)
KW - photovoltaic
UR - http://www.scopus.com/inward/record.url?scp=85193798317&partnerID=8YFLogxK
U2 - 10.1109/AIMS61812.2024.10512713
DO - 10.1109/AIMS61812.2024.10512713
M3 - Conference contribution
AN - SCOPUS:85193798317
T3 - International Conference on Artificial Intelligence and Mechatronics System, AIMS 2024
BT - International Conference on Artificial Intelligence and Mechatronics System, AIMS 2024
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2024 International Conference on Artificial Intelligence and Mechatronics System, AIMS 2024
Y2 - 22 February 2024 through 23 February 2024
ER -