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Innovative Hybrid War Strategy Optimization with Incremental Conductance for Maximum Power Point Tracking in Partially Shaded Photovoltaic Systems Cover

Innovative Hybrid War Strategy Optimization with Incremental Conductance for Maximum Power Point Tracking in Partially Shaded Photovoltaic Systems

Power Electronics and Drives
Volume 10 (2025): Issue 1 (January 2025)
By: ,  ,   and    
Open Access
|Dec 2024
Figures & tables

Figures & Tables

Figure 1.

General PV conversion chain. PV, photovoltaic.

Table 1.

Electrical specifications of the PV panels.

PmaxVocIscVmpImp
PV module213.15 W36.3 V7.84 A29 V7.35 A
PV installation426.3 W72.6 V7.84 A58 V7.35 A

[i] Imp, output current at the MPP under STC; Isc, short circuit current under STC; Pmax, maximum power output under STC; PV, photovoltaic; STC, standard test conditions; Vmp, voltage at the MPP under STC; Voc, open circuit voltage under STC.

Table 2.

Electrical specifications of the boost converter.

ParameterNounValue
Boost converter
LInductance (mH)1.1478
CinInput capacitor (µF)6,800
CoutOutput capacitor (µF)3,300
FPWM frequency (kHz)10
Load
RResistive load (Ω)100

[i] PWM, pulse width modulation.

Figure 2.

Equivalent circuit diagram of solar cell.

Figure 3.

Configuration of PV modules under different static PSCs. (A) Scenario 1—STC. (B) Scenario 2. (C) Scenario 3. (D) Scenario 4. PSCs, partial shading conditions; PV, photovoltaic; STC, standard test conditions.

Figure 4.

Flowchart of WSO algorithm. WSO, war strategy optimization.

Figure 5.

Flowchart of hybrid WSO-IC Algorithm. WSO-IC, war strategy optimization-incremental conductance.

Figure 6.

Diagram of the 426.3 W peak power PV system simulated in SIMULINK. PV, photovoltaic.

Table 3.

Optimal duty cycle calculated for each scenario

ScenarioPmpp (W)D_opt
Scenario 1Pmpp = 426.3D_opt_G = 0.71721425
Scenario 2Pmpp_G = 207.4D_opt_G = 0.80383836
Pmpp_L = 189.5D_opt_L = 0.54699656
Scenario 3Pmpp_G = 187.6D_opt_G = 0.55062217
Pmpp_L = 167.3D_opt_L = 0.77950357
Scenario 4Pmpp_G = 184.6D_opt_G = 0.55110705
Pmpp_L = 126.1D_opt_L = 0.74620251

[i] Pmpp_G: Power output in global peak point.

[ii] Pmpp_L: Power output in local peak point.

[iii] D_opt_G: Optimal duty cycle corresponding to global peak point using Eq. (6).

[iv] D_opt_L: Optimal duty cycle corresponding to local peak point using Eq. (6).

Figure 7.

Power Ppv and duty cycle under standard conditions (Scenario 1-STC). STC, standard test conditions.

Figure 8.

Power Ppv and duty cycle under PSCs (Scenario 2). PSCs, partial shading conditions.

Figure 9.

Power Ppv and duty cycle under PSCs (Scenario 3). PSCs, partial shading conditions.

Figure 10.

Power Ppv and duty cycle under PSCs (Scenario 4). PSCs, partial shading conditions.

Table 4.

Comparison of algorithm performance across different scenarios

AlgorithmConvergence time (ms)Duty cycleTracking error (%)Ppv (w)Efficiency (%)
Scenario 1: Ir1 = Ir2 = 1000 W/m2, T1 = T2 = 25 C, Pmpp = 426.3 W, Dopt G = 0.71721435
IC648.6890.71030.9641426.13099.96
P&O628.2760.71080.8943426.12499.96
WSO352.3680.71010.9919426.10699.95
WSO-IC398.4370.71160.7828426.14899.96
Scenario 2: Ir1 = 1000 W/m2, Ir2 = 400 W/m2, T1 = T2 = 25 C, Pmpp G = 207.4 W, Dopt G = 0.80383836
IC768.9020.530534.0041189.45391.35
P&O517.4830.530833.9668189.45091.35
WSO254.5450.79251.4105204.70598.70
WSO-IC271.3290.79381.2488207.35699.98
Scenario 3: Ir1 = 800 W/m2, Ir2 = 400 W/m2, T1 = T2 = 25 C, Pmpp G = 187.6 W, Dopt G = 0.55062217
IC567.8320.770439.9145167.00089.02
P&O405.5940.769939.8236167.20089.13
WSO271.3290.771440.0961167.20089.13
WSO-IC442.2810.53133.5092187.600100.00
Scenario 4: Ir1 = 600 W/m2, Ir2 = 400 W/m2, T1 = T2 = 25 C, Pmpp G = 184.6 W, Dopt G = 0.55110705
IC623.7760.740134.2933125.80068.15
P&O433.5660.740034.2752125.90068.20
WSO338.4620.739134.1119125.70068.09
WSO-IC492.3500.53782.4146184.50099.95

[i] IC, incremental conductance; P&O, perturb and observe; WSO, war strategy optimization; WSO-IC, war strategy optimization-incremental conductance.

Figure 11.

Quantitative comparison between the performances of IC, P&O, WSO, and WSO-IC methods for different shading patterns. (A) Duty cycle tracking error and (B) power extraction efficiency. IC, incremental conductance; P&O, perturb and observe; WSO, war strategy optimization; WSO-IC, war strategy optimization-incremental conductance.

Table 5.

Performance comparison of the proposed WSO-IC with different MPPT algorithms

MPPT algorithmEfficiency (%)Tracking time (s)
P&O (Khatib and Muhsen, 2020)96.080.321
FL (Khatib and Muhsen, 2020)96.940.35
PSO (Khatib and Muhsen, 2020)99.620.50
GWO (Berttahar et al., 2024)97.080.78
HOA (Berttahar et al., 2024)99.760.33
WSO-IC99.960.398

[i] FL, fuzzy logic, GWO, grey wolf optimization; MPPT, maximum power point tracking; P&O, perturb and observe; PSO, particle swarm optimization; HOA, horse herd optimization algorithm; WSO-IC, war strategy optimization-incremental conductance.

DOI: https://doi.org/10.2478/pead-2025-0001 | Journal eISSN: 2543-4292 | Journal ISSN: 2451-0262
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Language: English
Page range: 1 - 18
Submitted on: Sep 18, 2024
Accepted on: Nov 15, 2024
Published on: Dec 21, 2024
Published by: Wroclaw University of Science and Technology
In partnership with: Paradigm Publishing Services
Keywords:
photovoltaic system,
maximum power point tracking,
war strategy optimization,
incremental conductance
Related subjects:
Computer sciences,
Artificial intelligence,
Engineering,
Electrical engineering,
Electronics

© 2024 Hechmi Khaterchi, Chiheb Ben Regaya, Ahmed Jeridi, Abderrahmen Zaafouri, published by Wroclaw University of Science and Technology
This work is licensed under the Creative Commons Attribution 4.0 License.

Volume 10 (2025): Issue 1 (January 2025)
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