The main objective of this study is to optimize the long-term performance of an existing active-indirect solar hot water plant (SHWP), which supplies hot water at 65 °C for use in a flight kitchen, using a micro genetic algorithm in conjunction with a relatively detailed model of each component in the plant and solar radiation model based on the measured data. The performance of SHWP at Changi International Airport Services (CIASs), Singapore, is studied for better payback period using the monthly average hourly diffuse and beam radiations and ambient temperature data. The data input for solar radiation model is obtained from the Singapore Meteorological Service (SMS), and these data have been compared with long-term average data of NASA (surface meteorology and solar energy or SSE). The comparison shows a good agreement between the predicted and measured hourly-averaged, horizontal global radiation. The SHWP at CIAS, which comprises 1200m 2 of evacuated-tube collectors, 50m 3 water storage tanks and a gas-fired auxiliary boiler, is first analyzed using a baseline configuration, i.e., (i) the local solar insolation input, (ii) a coolant flow rate through the headers of collector based on ASHRAE standards, (iii) a thermal load demand pattern amounting to 100m 3/day, and (iv) the augmentation of water temperature by auxiliary when the supply temperature from solar tank drops below the set point. A comparison between the baseline configuration and the measured performance of CIAS plant gives reasonably good validation of the simulation code. Optimization is further carried out for the following parameters, namely; (i) total collector area of the plant, (ii) storage volume, and (iii) three daily thermal demands. These studies are performed for both the CIAS plant and a slightly modified plant where the hot water supply to the load is adjusted constant at times when the water temperature from tank may exceed the set temperature. It is found that the latter configuration has better thermal and economic performances over the conventional design.
All Science Journal Classification (ASJC) codes
- Renewable Energy, Sustainability and the Environment
- Materials Science(all)