Probabilistic approach for uncertainty-based optimal design of chiller plants in buildings

Conventional design of chiller plant is typically based on the peak cooling loads of buildings, while the cooling load reaches its peak level for only a small proportion of time in a year. This results in that even a perfectly designed chiller plant could be very significantly oversized in actual operation and it thus causes significant energy wastes. In this paper, an uncertainty-based optimal design based on probabilistic approach is proposed to optimize the chiller plant design. It ensures that the chiller plant operate at a high efficiency and the minimum annual total cost (including annual operational cost and annual capital cost) could be achieved under various possible cooling load conditions, considering the uncertain variables in cooling load calculation (i.e., weather conditions). On the premise of determining the minimum sufficient number of Monte Carlo simulation, this method maximizes the operating COP (coefficient of performance) and minimizing the annual total cost. A case study on the chiller plant of a building in Hong Kong is conducted to demonstrate the design process and validate the uncertainty-based optimal design method.