In the design of renewable energy capacity, due to the existence of weather uncertainty, the conventional design method can easily lead to overdesign or unsatisfactory performance in order to ensure the system is completely reliable. Most existing solar heating system (SHS) design optimization studies are based on deterministic data or information. However, weather uncertainty is one of the key factors affecting the reliability of the system and the rationality of design results. Therefore, this study proposed a multi-objective optimal design method for SHS considering the uncertainty of the weather and reliability of the system. Taking a SHS of an office building in Tianjin as an example, based on the actual meteorological parameters of 20 years, the uncertainty of the performance of buildings and equipment are simulated by TRNSYS and EnergyPlus. Multi-objective optimization under economic, environment and reliability of the system are considered in optimization algorithm. The optimization results show that compared with the conventional fchart method, total annual cost and CO2 emissions are respectively reduced by 8.3% and 2.5%. Compared with the exhaustive method, it can shorten the calculation time by 98.5%, which can greatly improve the efficiency of optimization.
Keywords solar heating system, optimization, weather, uncertainty, reliability