Cost optimization for a large-scale hybrid central cooling plant with multiple energy sources under a complex electricity cost structure

Abstract

Cooling energy costs can account for a significant portion of the total energy costs during summer for a large organization. A hybrid energy system or thermal energy storage can be used to reduce the energy cost. However, without proper operation plans, the advantage of using such systems could be limited. This article presents an energy cost optimization model for a hybrid cooling system under a complex energy cost structure. The model can handle a realistic non-linear complex cost structure incorporating the costs from electricity use, electrical demand, electricity demand ratchet, and fuel consumption. This article also examines the trade-off between chiller operations using different energy sources. The optimization model is constructed as a mixed-integer non-linear program. To reduce computational intensity, a dual-stage solution method is developed by treating a decision variable of the electricity demand limit temporarily as a constraint parameter. This reduced computation allows for the possibility of using the optimization model for real-time implementation. A case study of the central cooling system of an academic institution during a summer month showed that the developed method and model could be used for optimized operation to save energy costs significantly.