This dissertation proposed a new methodology for determining the optimal operating strategies for a chilled water storage system under a Time-of-Use electricity rate structure. It is based on a new classification of operating strategies and an investigation of multiple search paths. Each operating strategy consists of a control strategy and the maximum number of chillers running during the off-peak and on-peak periods. For each month, the strategy with the lowest monthly billing cost and minimal water level higher than the setpoint is selected as the optimal operating strategy for the current month. A system model is built to simulate the tank water level at the end of each time step and the system total power during each time step. This model includes six sub-models. Specifically, the plant model is a forward model using a wire-to-water concept to simulate the plant total power. For the Thermal Energy Storage (TES) model, the tank state is described with total chilled water volume in the tank and its derivation is the tank charging or discharging flow rate. A regression model is adopted to simulate the loop supply and return temperature difference as well as the loop total flow rate demand. In the control strategy sub-model, except for three conventional control strategies and the operation without TES, a new control strategy is advanced to load the chiller optimally. The final results will be a table showing the monthly control strategy and maximal number of chillers staged on during the off-peak and on-peak periods, an approach which is easy for the operators to follow. Two project applications of this methodology are introduced in this dissertation. One is an existing TES system with state-of-the-art control and metering systems. The monthly optimal operating strategies are generated, which will achieve significant savings. The comparisons among different control strategies are also provided. The other application consists of multiple plants with little data. The purpose of the study is to evaluate the economic feasibility of designing a new chilled water storage tank and sharing it among four plants. This problem can be solved with a simplified system model, and an optimal tank size is recommended.

Optimal chiller loading (OCL) is described as a means to improve the energy efficiency of a chiller plant operation. It is formulated as a multi-period constrained mixed integer non-linear optimization problem to optimize the total cooling load distribution through accurate chiller models. OCL is solved as a set of quadratic programs using sequential programming algorithm (SQP) in MATLAB. Based on application of the methodology to chiller systems at UT Austin and a semiconductor manufacturing facility, OCL can result in an annual energy savings of about 8%. However, the savings may reduce considerably in case of additional physical constraints on overall plant operation. With the addition of thermal energy storage (TES) to the system, OCL can reduce the daily cooling costs in the case of time varying electricity prices by 13.45% on an average. The energy efficiency of a chiller plant as a function of its chiller arrangement is studied by using fitted chiller models. If all other variables are kept same, chillers operating in parallel consume up to 9.62% less power as compared to when they are operated in series. Otherwise, chillers may operate up to 12.26% more efficiently in series depending on their chilled water outlet temperature values. The answer to the optimal chiller arrangement can be straightforward in some cases or can be a complex optimization problem in others. / text