Life-Cycle Optimization of a Chiller Plant with Quantified Analysis of Uncertainty and Reliability in Commercial Buildings

Featured Application Proper design of a chiller plant is considered as one of the most effective ways to reduce the energy consumption of commercial buildings. Due to the improper treatment of uncertainty and reliability, existing design methods in practice often result in oversized systems. This paper proposes a design optimization method for chiller plants based on life-cycle total cost minimization with quantified analysis of uncertainty and reliability. It can ensure a chiller plant operates at its high efficient region under various cooling load conditions and provide sufficient cooling capacity even some equipment/systems with failures. Abstract Conventional and most optimal design methods for chiller plants often address the annual cooling load distribution of buildings and their peak cooling loads based on typical meteorological year (TMY) data, while the peak cooling load only appears a few times during the life-cycle and the sized chiller plant usually operates within its low efficient region. In this paper, a robust optimal design method based on life-cycle total cost was employed to optimize the design of a chiller plant with quantified analysis of uncertainty and reliability. By using the proposed design method, the optimized chiller plant can operate at its highly efficient region under various cooling load conditions, and provide sufficient cooling capacity even alongside some equipment/systems with failures. The minimum life-cycle total cost, which consists of the capital cost, operation, and availability-risk cost, can be achieved through optimizing the total cooling capacity and the numbers/sizes of chillers. A case study was conducted to illustrate the detailed implementation process of the proposed method. The performance of this design method was evaluated by comparing with that of other design methods.