Open Access

ARTICLE

Thermal-Electrical Modeling and Comparative Analysis of Power Prediction for Bifacial and Monofacial Photovoltaics

Man Fan¹, Yifang Li¹, Yang Qiao¹, Yin Zhang^2,*, Bowen Xu^1,*, Xiangfei Kong¹, Han Li¹, Ramy Rabie³, Tamer M. Mansour⁴
1 School of Energy and Environmental Engineering, Hebei University of Technology, Tianjin, China
2 The Institute of Seawater Desalination and Multipurpose Utilization, MNR (Tianjin), Tianjin, China
3 Mechanical Engineering Department, Faculty of Engineering, Suez Canal University, Ismailia, Egypt
4 Egyptian Chinese College for Applied Technology, Suez Canal University, Ismailia, Egypt
* Corresponding Author: Yin Zhang. Email: ; Bowen Xu. Email:

Energy Engineering https://doi.org/10.32604/ee.2026.077085

Received 02 December 2025; Accepted 13 February 2026; Published online 16 March 2026

Abstract

Bifacial photovoltaic (bPV) harnesses solar energy from both sides, significantly enhancing power generation. However, accurate and rapid power estimation for bPV remains challenging as most research has focused on monofacial photovoltaic (mPV). Unlike mPV, the power output of bPV is significantly influenced by complex thermal behavior due to bilateral energy absorption, necessitating models coupling thermal and electrical performance. This study firstly tested the thermal and electrical properties of mPV and bPV under various meteorological conditions. Five power estimation models were then developed and compared, including two linear models, two simplified single-diode models (SDM), and one complete SDM. Crucially, the module temperature was calculated using multiple empirical formulas that incorporated both unilateral and bilateral irradiance inputs to better represent the distinct thermal environments. For mPV, the predicted power errors ranged from 2.94 to 33.72 W (−23.21% to 6.36%) relative to a peak power of 389.82 W. For bPV, errors ranged from 1.88 to 35.36 W (−23.28% to 0.26%) relative to a peak power of 399.30 W. Analysis revealed that the accuracy of power prediction was highly sensitive to the method of temperature estimation, underscoring the importance of thermal modeling. Among the models, the complete SDM demonstrated the most robust performance for bPV, effectively handling the interplay between bilateral irradiance and the resulting thermal state, with error variations maintained within 11.19 to 12.91 W (19.79% to 37.96%) across different parameter sets.

---

Keywords

Monofacial and bifacial photovoltaics; thermal-electrical modeling; parameters simplification; power prediction; outdoor experiment

---