Incremental Conductance Based Particle Swarm Optimization Algorithm for Global Maximum Power Tracking of Solar-PV under Nonuniform Operating Conditions
Abstract
:1. Introduction
- Design and application of ICPSO algorithm for extraction of efficient tracking the global maximum power point under NUOC.
- Proposed algorithm is effective to reduce the steady-state oscillations by continuous tracking of weight component.
- Proposed algorithm updates velocity and position of particles using the concept of I&C MPPT algorithm.
- Proposed ICPSO is useful for fast-tracking of the speed with negligible oscillations at the global maximum point compared to other conventional and hybrid MPP algorithms.
- Easy calculation for accurate tracking of global maximum during sudden fluctuations in temperature and irradiance level.
- MATLAB code has been successfully executed for various temperatures and Irradiation condition of Solar-PV array in a practical scenario.
2. Concept Behind the Proposed ICPSO Algorithm
3. System under Consideration
4. Design and Implementation of Proposed MPPT Algorithm
4.1. Concept of Incremental Conductance (I & C)
- →
- Operation point is at maximum power point (MPP)
- →
- Operation point is at left side of MPP
- →
- Operation point is at right side of MPP
4.2. Incremental Conductance Based Particle Swarm Optimization (ICPSO)
5. Concept Validation
5.1. Scenario-1→Irradiance 1000 W/m, Temperature 25 C
5.2. Scenario-2→Irradiance 300 W/m, Temperature 25 C
5.3. Scenario-3→Irradiance 1000 W/m, Temperature 30 C
5.4. Scenario-4→Irradiance 300 W/m, Temperature 30 C
5.5. Duty Cycle Updation under Different Irradiance Conditions
6. Comparative Performance Analysis
7. Conclusions
Author Contributions
Funding
Conflicts of Interest
Appendix A
References
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MPPT Algorithms | SPV Output Power at Fix 25 °C | ||
---|---|---|---|
1000 W/m | 600 W/m | 300 W/m | |
P&O Algorithm [28] | 90.13 kW | 53.68 kW | - |
I&C Algorithm [28] | 94.52 kW | 56.29 kW | - |
GA-based optimized FLC [28] | 95.11 kW | 56.14 kW | - |
PSO-based optimized FLC [28] | 96.15 kW | 56.78 kW | - |
PSO-GA-based optimized FLC [28] | 98.85 kW | 58.64 kW | - |
Proposed ICPSO | 97.3 W | 60 W | 94.2 W |
MPPT Algorithms | SPV Output Power at Fix 1000 W/m | Remarks | |
---|---|---|---|
25 °C | 30 °C | ||
P&O Algorithm [28] | 90.13 kW | 86.73 kW | Conventional |
I&C Algorithm [28] | 94.52 kW | 90.91 kW | Conventional |
GA-based optimized FLC [28] | 95.09 kW | 89.56 kW | Large training data required |
PSO-based optimized FLC [28] | 96.03 kW | 90.1 kW | computational complexity |
PSO-GA-based optimized FLC [28] | 98.7 kW | 94.47 kW | Increases up to 8% of output power with high computation time |
Proposed ICPSO | 97.3 W | 92.4 W | Increases up to 7% of output power with low computation time |
MPPT Algorithms | Tracking Time in Simulation (Second) |
---|---|
Firefly [11] | 0.2 |
Overall distribution (OD)- PSO [11] | 0.21 |
P&O-PSO [11] | 0.28 |
High performance MPP [25] | 0.3 |
Load-current adaptive step-size and perturbation frequency (LCASF) [24] | 0.35 |
PSO-GA based optimized FLC [28] | ≈0.15 |
Proposed ICPSO | 0.1 |
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Singh Chawda, G.; Prakash Mahela, O.; Gupta, N.; Khosravy, M.; Senjyu, T. Incremental Conductance Based Particle Swarm Optimization Algorithm for Global Maximum Power Tracking of Solar-PV under Nonuniform Operating Conditions. Appl. Sci. 2020, 10, 4575. https://doi.org/10.3390/app10134575
Singh Chawda G, Prakash Mahela O, Gupta N, Khosravy M, Senjyu T. Incremental Conductance Based Particle Swarm Optimization Algorithm for Global Maximum Power Tracking of Solar-PV under Nonuniform Operating Conditions. Applied Sciences. 2020; 10(13):4575. https://doi.org/10.3390/app10134575
Chicago/Turabian StyleSingh Chawda, Gajendra, Om Prakash Mahela, Neeraj Gupta, Mahdi Khosravy, and Tomonobu Senjyu. 2020. "Incremental Conductance Based Particle Swarm Optimization Algorithm for Global Maximum Power Tracking of Solar-PV under Nonuniform Operating Conditions" Applied Sciences 10, no. 13: 4575. https://doi.org/10.3390/app10134575
APA StyleSingh Chawda, G., Prakash Mahela, O., Gupta, N., Khosravy, M., & Senjyu, T. (2020). Incremental Conductance Based Particle Swarm Optimization Algorithm for Global Maximum Power Tracking of Solar-PV under Nonuniform Operating Conditions. Applied Sciences, 10(13), 4575. https://doi.org/10.3390/app10134575