Facilitate the design of residential PV using reliability-based design optimization

Zilong Zhao, Guoquan Lv and Yanwen Xu

Renewable Energy, 2025, vol. 240, issue C

Abstract: For the first time, the sizing optimization on rooftop PV integrates probabilistic uncertainties and reliability analysis. This study proposes a reliability-based design optimization (RBDO) that treats PV installation angle as a design variable and aims to minimize installation area. Constraints were established to regulate the variable range during the optimization process—the overall power generation ratio, self-use power ratio, and increase of back panel temperature. In the meantime, the environmental variables, including the solar irradiance and ambient temperature, as well as the random variables in PV system, such as the nominal efficiency, are considered with their intrinsic uncertainties. Compared to a deterministic optimization where all input variables are treated as exact values that may lead to non-optimal designs under non-idealized conditions, the RBDO algorithm is proved effective in identifying a design that meets performance requirements and even maintains a high probability of confidence under uncertain conditions. By varying the minimum requirements on power ratios, threshold of back panel temperature limit and probability indices by scenarios, the optimal installation angle and the installation area of PV array are obtained. The results indicated that the uncertainty levels accompanied by the three constraint functions impose a significant influence on the sizing of PV array.

Keywords: PV system; Reliability-based optimization; Uncertainties; Probabilistic modeling; Cost minimization (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:240:y:2025:i:c:s0960148124022122

DOI: 10.1016/j.renene.2024.122144

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