Tilt Angle and Inverter Input Voltage Optimization for Rooftop Photovoltaic Systems using Whale Optimization

Abstract

Optimizing the performance of rooftop photovoltaic (RTPV) systems is crucial maximize energy production, especially in limited urban spaces. The main problem with the 122,040 Wp RTPV system is a significant performance gap, where the peak output power only reaches 95.93 kW, suggesting that the operational configuration may not be at the optimal point. The novelty of this research lies in the simultaneous optimization of two critical parameters: the geometric tilt angle (β) and the electrical inverter input voltage (V_DC), a dual-parameter approach that contrasts with prior studies focusing on single-parameter optimization. This study aims to determine the optimal power output by employing the Whale Optimization Algorithm (WOA). The WOA method was selected for its superior ability to navigate complex search spaces by mimicking the bubble-net hunting strategy of humpback whales through a spiral model and a shrinking encircling mechanism to identify the global optimum. Simulation results show that convergence is achieved at the 75th iteration. The optimization results demonstrate a significant performance improvement, increasing the output power from 95.93 kW to 105.01 kW, which represents a 9.46% efficiency gain. This simultaneous optimization, resulting in a panel β of 26.26° and V_DC of 629.66 V, proves to be a robust technical contribution for shifting the operating point toward the global maximum power point (GMPP) in industrial-scale RTPV systems.

Keywords

Solar energy; photovoltaic systems; whale optimization algorithm; inverter input voltage; tilt angle optimization.

References

M. S. Azam et al., “Performance enhancement of solar PV system introducing semi-continuous tracking algorithm based solar tracker,” Energy, vol. 289, p. 129989, Feb. 2024. https://doi.org/10.1016/j.energy.2023.129989

R. Senthil, “A technical note on integrating thermal energy systems into solar photovoltaic panels toward a circular economy,” Renew. Energy Focus, vol. 42, pp. 97–100, Sep. 2022. https://doi.org/10.1016/j.ref.2022.06.002

R. Nasr, B. Abou-Zalam, and E. Nabil, “Metaheuristic optimization algorithm-based enhancement of photovoltaic energy system performance,” Arab. J. Sci. Eng., vol. 48, no. 11, pp. 14789–14810, Nov. 2023. https://doi.org/10.1007/s13369-023-07847-0

L. He, B. Zhao, F. Rong, B. Zhu, M. Xu, and L. Wang, “An innovative metaheuristic algorithm for photovoltaic tilt angle optimization,” Sci. Rep., vol. 15, Art. no. 28391, Dec. 2025. https://doi.org/10.1038/s41598-025-28391-x

A. Hadj Slama et al., “Metaheuristic optimization of hybrid renewable energy systems under asymmetric cost–reliability objectives,” Symmetry, vol. 17, no. 9, Art. no. 1412, 2025. https://doi.org/10.3390/sym17091412

S. M. Bozorgi and S. Yazdani, “IWOA: An improved whale optimization algorithm for optimization problems,” J. Comput. Des. Eng., vol. 6, no. 3, pp. 243–259, Jul. 2019. https://doi.org/10.1016/j.jcde.2019.02.002

S. Mirjalili and A. Lewis, “The whale optimization algorithm,” Adv. Eng. Softw., vol. 95, pp. 51–67, May 2016. https://doi.org/10.1016/j.advengsoft.2016.01.008

S. Angadi, U. R. Yaragatti, Y. Suresh, and A. B. Raju, “System parameter-based performance optimization of solar PV systems with perturbation-based MPPT algorithms,” Energies, vol. 14, no. 7, Art. no. 2007, Apr. 2021. https://doi.org/10.3390/en14072007

J. P. Murcia Leon et al., “HyDesign: A tool for sizing optimization of grid-connected hybrid power plants including wind, solar photovoltaic, and lithium-ion batteries,” Wind Energy Sci., vol. 9, pp. 759–776, Apr. 2024. https://doi.org/10.5194/wes-9-759-2024

Sameera, M. Tariq, M. Rihan, and M. Ayan, “A comprehensive review on the application of recently introduced optimization techniques obtaining maximum power in the solar PV system,” Renew. Energy Focus, vol. 49, Art. no. 100564, Jun. 2024. https://doi.org/10.1016/j.ref.2024.100564

A. Alsharif, A. A. Ahmed, M. M. Khaleel, Y. Nassar, M. A. Sharif, and H. J. El-Khozondar, “Whale optimization algorithm for renewable energy sources integration considering solar-to-vehicle technology,” in Proc. 2023 IEEE 9th Int. Women in Eng. Conf. Electr. Comput. Eng. (WIECON-ECE), Nov. 2023, pp. 397–401. https://doi.org/10.1109/WIECON-ECE60392.2023.10456379

M. G. Babu and P. S. R. Nayak, “Entropy-based controller parameter optimization for a dual-input EV charger integrated with WPT and solar energy using the whale optimization algorithm,” Control Eng. Pract., vol. 164, Art. no. 106432, Nov. 2025. https://doi.org/10.1016/j.conengprac.2025.106432

C. Xie, Y. Dong, N. Liu, W. Zhou, J. Chu, and Y. Tang, “Energy consumption prediction for solar greenhouse based on whale optimization extreme learning machine: Integration of heat balance model and intelligent algorithm,” AgriEngineering, vol. 7, no. 11, Art. no. 393, Nov. 2025. https://doi.org/10.3390/agriengineering7110393

I. Challouf et al., “Optimization of photovoltaic system performance under shading conditions through hybrid storage,” in Proc. 2024 IEEE Int. Conf. Adv. Syst. Emergent Technol. (IC_ASET), Apr. 2024, pp. 1–6. https://doi.org/10.1109/IC_ASET61847.2024.10596253

N. Lu and J. Qin, “Optimization of tilt angle for PV in China with long-term hourly surface solar radiation,” Renew. Energy, vol. 229, Art. no. 120741, Aug. 2024. https://doi.org/10.1016/j.renene.2024.120741

A. P. F. B. Maniraj, “PV output power enhancement using whale optimization algorithm under normal and shading conditions,” Int. J. Renew. Energy Res., vol. 10, no. 3, 2020. https://doi.org/10.20508/ijrer.v10i3.11098

L. Iturralde Carrera, G. A. Francia, C. Robles, J. Terven, E. Chávez-Urbiola, and J. Rodriguez, “Advances and optimization trends in photovoltaic systems: A systematic review,” AI, vol. 6, Art. no. 225, Sep. 2025. https://doi.org/10.3390/ai6090225

L. P. Sivakumar, S. Sivakumar et al., “Implementation of particle swarm optimization for maximum power absorption from photovoltaic system using energy extraction circuit,” in Proc. 2019 IEEE Int. Conf. Intell. Techn. Control, Optim. Signal Process. (INCOS), Apr. 2019, pp. 1–4. https://doi.org/10.1109/INCOS45849.2019.8951378

S. A. Kalogirou, Solar Energy Engineering: Processes and Systems. Academic Press, 2023. https://doi.org/10.1016/C2021-0-02041-1

B. Aryaseta et al., “The influence of tilt angle on the daily profile total energy of photovoltaic polycrystal,” Jurnal Pena Sains, vol. 11, no. 1, pp. 9–17, Apr. 2024.

http://dx.doi.org/10.28989/avitec.v8i1.3792

Article Metrics

Abstract view: 15 times

This work is licensed under a Creative Commons Attribution 4.0 International License.

Refbacks

• There are currently no refbacks.