Multi-Scale Modeling of Power Plant Performance Enhancement Using Asynchronous Thermal Storage and Heat Rejection

Abstract

The study summarized in this paper links a model of thermal energy storage (TES) unit performance to a subsystem model including heat exchangers that cool down the storage at night when air temperatures are low; this cool storage is subsequently used to precool the air flow for a power plant air-cooled condenser during peak daytime air temperatures. The subsystem model is also computationally linked to a model of Rankine cycle power plant performance to predict how much additional power the plant could generate as a result of the asynchronous cooling augmentation provided by this subsystem. The goal of this study is to use this model to explore the parametric effects of changing phase change material (PCM), melt temperature, and the energy input and rejection control settings for the system. With this multi-scale modeling, the performance of the TES unit was examined within the context of a larger subsystem to illustrate how a high efficiency, optimized design target can be established for specified operating conditions that correspond to a variety of applications. Operating conditions of interest are the mass flow rate of fluid through the flow passages within the TES, the volume of the TES, and the amount of time the system remains in the extraction process in which thermal energy is inputted to the device by melting PCM, and the PCM melt temperature. These conditions were varied to find combinations that maximized efficiency for a 50 MW power plant operating in the desert regions of Nevada during an average summer day. By adjusting the flow rate within the fluid flow passages and the volume of the TES to achieve complete melting of the PCM during a set extraction time, indications of the parametric effects of system flow, melt temperature, and control parameters were obtained. The results suggest that for a full-sized power plant with a nominal capacity of 50 MW, the kWh output of the plant can be increased by up to 3.25% during the heat input/cold extraction period, depending on parameter choices. Peak power output enhancements were observed to occur when the system operated in the extraction phase during limited hours near the peak temperatures experienced throughout a day, while total kWh enhancement was shown to increase as the extraction period increased. For the most optimized conditions, cost analyses were performed, and it was estimated that the TES system has the potential to provide additional revenue of up to $1,366 per day, depending on parameter choices as well as the local cost of electricity. Results obtained to date are not fully optimized, and the results suggest that with further adjustments in system parameters, weather data input, and control strategies, the predicted enhancement of the power output can be increased above the results in the initial performance predictions reported here.

Comparison of Model Predictions and Performance Test Data for a Prototype Thermal Energy Storage Module

“…The methodology and results that are presented in this paper are built upon a larger body of work from this group over the last several years [6][7][8][9][10]. The first of these contains the derivation of a non-dimensional framework developed in order to analyze thermal energy storage technology [6].…”

“…This problem was mathematically challenging by introducing spatially varying initial conditions (due to the nature of cyclic melting and freezing processes) as well as a transient boundary condition (for the varying working fluid temperature from the heat exchangers) [9]. The system equations derived in this paper were applied to model the performance of a power plant using TES for asynchronous cooling of a Rankine cycle steam condenser [10]. This paper demonstrated the economic viability of thermal storage and all that remains is to validate the numerical framework used in previous explorations.…”