Volume 56

A Reliability-Based and Stochastic Optimization for Balancing Capacity and Uncertainties in a Roof-Mounted Photovoltaic (PV) System Zilong Zhao, Guoquan Lv, Yanwen Xu, Pingfeng Wang

Abstract

Photovoltaic (PV) systems are being increasingly adopted in buildings, but the installed capacity often fails to account for uncertainties during the usage phase. A novel probabilistic optimization model based on the reliability level is applied to size the PV arrays on a residential building. The minimum total installation area of the PV panels is treated as the objective of the optimization. To consider the impacts of various uncertainties during the installation and continuous operations of PV system, a design variable, installation angle, and multiple environmental variables, including annual solar irradiation, ambient temperature, and attenuation rate on the system efficiency, are integrated into the model. A unique statistic profile of uncertainty is established for each of the variables based on the verifications from the documented literature. In the meantime, to concurrently ensure the sufficient electricity supply provided by the PV system and mitigating the system degradation, constraints on the total power generation, self-use power ratio, and temperature increase were formulated. By establishing different levels of confidential reliability and magnitudes of uncertainties associated with design and random variables, the optimized size and installed angle of PV exhibited significantly different results.

Keywords solar energy, design optimization, reliability, probabilistic model, building energy