Determining the economic design radiation for a solar heating system through uncertainty analysis

Abstract

Uncertainties, which are introduced by environmental conditions in renewable systems, result in unstable energy supply and demand. For a solar heating system, the seasonal variation in the ambient temperature and radiation critically influence system performance. Meanwhile, the current design parameters for improving robustness, based on the empirical tolerance, are unreasonable, which can lead to an overestimation of the facility’s capacity. In addition, the effects of system control parameters, always assumed in the design stage, on the uncertainties of the system are not given more attention. In this study, a theoretical model was chosen to indicate the uncertainties of the design parameters in a complementary heating system by integrating solar energy and an air-source heat pump (ASHP), and a method was proposed to determine the design radiation by considering the uncertainties of the system. First, a Monte Carlo simulation was applied to propagate the input uncertainties of the solar fraction and system efficiency. Then, the input parameters were ordered by significance to the system performance based on sensitivity analysis, to improve the economic dependability of the design. Finally, the economic design radiation values of each district are decided under local calculated outdoor temperature of the enclosure structures in winter. Moreover, the proposed methodology could also be a guide for using uncertainties to determine the optimal design parameters for other renewable systems.