Optimization Under Uncertainty: A Case Study of a Solar Absorption Cooling and Heating System for a Medium-Sized Office Building in Atlanta

Abstract

Solar absorption cooling and heating (SACH) systems currently still stay at development and demonstration stage due to the nature of the complex system. It is critical for practitioners and engineers to have a correct and complete performance analyses and evaluation for SACH systems with respects of energy, economics, and environment. Optimization is necessarily involved to find the optimal system design by considering these three aspects. However, many assumptions made in the optimization are sensitive to the energy, economic, and environmental variations, and thus the optimization results will be affected. Therefore, the sensitivity and uncertainty analysis is important and necessary to make optimization robust. This paper uses a case study to explore the influence of the uncertainties on the SACH system optimization results. The case is a SACH system for a medium size office building in Atlanta. The one parameter at a time (OAT) sensitivity analysis method was applied firstly to determine the most sensitive inputs. Monte Carlo statistical method was utilized to generate the data sets for uncertainty analysis. The optimization problem under uncertainty was then formulated and solved. Due to the uncertainty associated with system inputs, the optimization solutions were found with certain types of the distributions. In addition, the scenario analysis on electricity price does not show large sensitivity to the objectives.