TY - GEN
T1 - A New and Reliable Objective Functions for Extracting the Unknown Parameters of Solar Photovoltaic Cell Using Political Optimizer Algorithm
AU - Premkumar, M.
AU - Sowmya, R.
AU - Jangir, Pradeep
AU - Siva Kumar, J. S.V.
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/10/26
Y1 - 2020/10/26
N2 - The primary issue in the design of photovoltaic (PV) systems is the availability of an exact PV model, and it emulates the PV cell behaviour. The precision of the PV model is based mainly on objective functions and optimization techniques. Based on this statement, this paper discusses two different objective functions to identify the unknown parameters of the solar cell using a novel Political Optimizer (PO) algorithm. The experimental values of the RTC France PV cell under 33°C and 1000 W/m2 environmental condition are considered to identify the unknown parameters of the single-diode model (SDM) and double-diode model (DDM). The ohmic resistances are neglected in forming the first objective function to reduce the computation time, whereas, the ohmic resistance is considered in forming second objective function to increase the accuracy. The simulation results are presented for the PO algorithm, and the performance comparison is made among Grey Wolf Optimizer (GWO) and Harris Hawk Optimizer (HHO) with the PO algorithm. The PO algorithm confirms the accurate result and delivers an improved illustration for the PV cell experimental data.
AB - The primary issue in the design of photovoltaic (PV) systems is the availability of an exact PV model, and it emulates the PV cell behaviour. The precision of the PV model is based mainly on objective functions and optimization techniques. Based on this statement, this paper discusses two different objective functions to identify the unknown parameters of the solar cell using a novel Political Optimizer (PO) algorithm. The experimental values of the RTC France PV cell under 33°C and 1000 W/m2 environmental condition are considered to identify the unknown parameters of the single-diode model (SDM) and double-diode model (DDM). The ohmic resistances are neglected in forming the first objective function to reduce the computation time, whereas, the ohmic resistance is considered in forming second objective function to increase the accuracy. The simulation results are presented for the PO algorithm, and the performance comparison is made among Grey Wolf Optimizer (GWO) and Harris Hawk Optimizer (HHO) with the PO algorithm. The PO algorithm confirms the accurate result and delivers an improved illustration for the PV cell experimental data.
UR - http://www.scopus.com/inward/record.url?scp=85100486764&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85100486764&partnerID=8YFLogxK
U2 - 10.1109/ICDABI51230.2020.9325627
DO - 10.1109/ICDABI51230.2020.9325627
M3 - Conference contribution
AN - SCOPUS:85100486764
T3 - 2020 International Conference on Data Analytics for Business and Industry: Way Towards a Sustainable Economy, ICDABI 2020
BT - 2020 International Conference on Data Analytics for Business and Industry
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2020 International Conference on Data Analytics for Business and Industry: Way Towards a Sustainable Economy, ICDABI 2020
Y2 - 26 October 2020 through 27 October 2020
ER -
