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As electrification and decarbonization goals become more commonplace across the country, theneed for integrating thermal energy storage (TES) with HVAC to provide flexibility and loadshifting is growing. Although there has been recent work related to the modeling and design ofTES-integrated heat pump (HP) systems, investigation of generalized sizing and control methodsfor these systems remain limited. This paper details the development of generalized controls andsizing strategies applicable across different TES-integrated designs, two of which are discussedin this study. We demonstrate how model-based design enables an informed sizing and controlsdesign process using the control-oriented Modelica language to generate high-fidelity modelsthat accurately represent real-world behavior.We detail our development and testing of both heuristic and model predictive control(MPC) algorithms to determine the optimal charge and discharge schedule with dynamic varyingutility prices. Experimental results show MPC provides operating costs reduction of nearly 20%for a minimum TES sizing scenario. In addition, we provide a generalized and intuitive controlalgorithm with near-optimal performance to control HP + TES systems and test its performancein simulation. This generalized control algorithm is also used to drive the results of our costanalysis, providing insights for engineers designing new TES-integrated HVAC systems. Thecost analysis demonstrates the tradeoff between higher initial hardware costs from largerequipment and the resulting operational cost benefits, and enables a cost-effective sizing methodwhich is applicable to any system. The paper concludes with design recommendations for newintegrated HP-TES control systems in buildings.

Traditional control sequences for HVAC systems in large commercial buildings havehistorically led to poor energy efficiency. To overcome this issue, ASHRAE has recentlypublished Guideline 36 (G36), a collection of high-performance control sequences aimed atreducing energy consumption and cost for building owners. While these sequences are effectivein increasing energy efficiency, their influence on a building's capacity to deliver demandflexibility remains uncertain. Prior research suggests a potential trade-off between energyefficiency and demand flexibility because permanently reducing energy use negatively impactsthe available amount of load that can be reduced when responding to grid signals. To investigatethis hypothesis, we created Modelica simulation models for an air handling unit with a G36trim-and-respond sequence, calibrated these models to a fully instrumented experimentalbuilding testbed X1A in FLEXLAB, and simulated different demand flexibility scenarios.Counter to expectations, results show that, during a “shed event” with prior pre-cooling, G36reduces demand by around 3.1 W/m2 more than the traditional control sequences, at the cost of areduction in comfort (1.5 °C-hour/day) across five different cities across the United States. Ourresults provide encouraging evidence that, under the tested conditions, G36 does not decreasedemand flexibility. This study should increase the confidence of building owners, designers, andoperators who are looking to take advantage of demand flexibility programs while complyingwith increasingly stringent building energy efficiency standards.

Thermal end uses dominate building energy consumption and are a major driver of peak demand. As heating is electrified, peak electrical power required will surge, prompting a need for innovative HVAC system designs and controls.These designs must incorporate novel technologies at the component level and new integration techniques at the system level. One such possibility involves the addition of thermal energy storage (TES) in heating and cooling equipment using a phase change material (PCM) heat exchanger. Here, thermal energy storage via phase change can be used to shift the HVAC system loads to times of lower electricity cost, reduced carbon intensity, and greater energy efficiency. Most of the current utilization of PCM in buildings involves passive components. By actively controlling when heat is stored and released from PCM, we can optimize the building HVAC system to cost-effectively meet consumer needs with the flexibility to draw on renewable energy resources when they are abundant and available.While this combination of technologies is promising in theory, simulation-based evaluation of a prototype can be difficult due to the modeling requirements at the component level and the large number of possible configurations and operating modes at the system level. To conduct this evaluation, we use the Modelica language for modeling and simulation because it enables users to represent the important physics of the problem, interchange and rearrange components in an efficient manner, and implement a range of control configurations. In this work, we considered three case studies: a portable building, a large commercial retail store, and a multifamily residential apartment unit. Each of these employs a different system design, ranging from a single package vertical unit incorporating PCM to a central plant with independent heat pump, evaporative cooling, and thermal energy storage components. This paper describes the technologies in question, presents modeling at the component and system levels, and demonstrates building energy and demand charge cost savings with local time-of-use tariffs in a hot-dry climate.

As we continue to electrify space- and water-heating, the electricity demand profile of manybuildings will change significantly, and periods of high electricity demand will likely not alignwith renewable energy generation. We expect electricity demands will increase substantiallyin the winter, annual maximum electricity demands will increase, and more regions willexperience annual peak electrical demands – and higher wholesale electricity prices – in thewinter. This is especially important for cold climates where 60% of site energy use in buildingsis for heating, and where heat pumps perform least efficiently. This paper focuses on onepromising solution among the many paths to electrification: the use of phase change materials(PCM) for compact low-cost thermal energy storage (TES). We present the design andsimulation of a combi heat pump and phase change thermal storage system used for space- andwater-heating in a multifamily residence in a cold climate. To assess the benefits of thistechnology, we compare its annual performance to that of a current state-of-the-art air-to-airheat pump and separate heat pump water heater. Simulation results for IECC Climate Zone 6Areveal that the combi heat pump with phase change thermal storage can reduce the design sizefor heat pumps by 40-60%, reduce maximum electric demand by 30-50%, reduce electricityuse during 4-12-hour load shed periods by 50%, and avoid the need for auxiliary electricresistance for both space- and water-heating. Tariff structures are highly varied betweendifferent utilities and currently reflect higher wholesale market prices for electricity duringsummer days. Consequently, although this system design provides large electric demandreductions during hypothetical 4-12-hour load shed periods, it does not provide energy costreductions with current winter residential time-of-use tariffs.

Thermal end uses dominate building energy consumption and are a major driver of peak demand. As heating is electrified, peak electrical power required will surge, prompting a need for innovative HVAC system designs and controls.These designs must incorporate novel technologies at the component level and new integration techniques at the system level. One such possibility involves the addition of thermal energy storage (TES) in heating and cooling equipment using a phase change material (PCM) heat exchanger. Here, thermal energy storage via phase change can be used to shift the HVAC system loads to times of lower electricity cost, reduced carbon intensity, and greater energy efficiency. Most of the current utilization of PCM in buildings involves passive components. By actively controlling when heat is stored and released from PCM, we can optimize the building HVAC system to cost-effectively meet consumer needs with the flexibility to draw on renewable energy resources when they are abundant and available.While this combination of technologies is promising in theory, simulation-based evaluation of a prototype can be difficult due to the modeling requirements at the component level and the large number of possible configurations and operating modes at the system level. To conduct this evaluation, we use the Modelica language for modeling and simulation because it enables users to represent the important physics of the problem, interchange and rearrange components in an efficient manner, and implement a range of control configurations. In this work, we considered three case studies: a portable building, a large commercial retail store, and a multifamily residential apartment unit. Each of these employs a different system design, ranging from a single package vertical unit incorporating PCM to a central plant with independent heat pump, evaporative cooling, and thermal energy storage components. This paper describes the technologies in question, presents modeling at the component and system levels, and demonstrates building energy and demand charge cost savings with local time-of-use tariffs in a hot-dry climate.

Although model predictions of thermal energy storage (TES) performance have been explored in previous investigations, relevant test data that enable experimental validation of performance models have been limited. This is particularly true for high-performance TES designs that facilitate fast input and extraction of energy. In this paper, we present a summary of experimental tests of a high-performance TES unit using lithium nitrate trihydrate phase change material as a storage medium. Performance data are presented for complete dual-mode cycles consisting of extraction (melting) followed by charging (freezing). These tests simulate the cyclic operation of a TES unit for asynchronous cooling in a variety of applications. The model analysis is found to agree reasonably well, within 10%, with the experimental data except for conditions very near the initiation of freezing, a consequence of subcooling that is required to initiate solidification.

An abundance of research has been performed to understand the physics of latent thermal energy storage with phase change material. Some analytical and numerical findings have been validated by experiments, but there are few free and open-source models available to the general public for use in systems simulation and analysis. The Modelica programming language is a good avenue to make such models available, because it is object-oriented, equation-based, declarative, and acausal. These characteristics have enabling the creation of component model libraries that can be used to build larger system simulations for design analysis. The authors have previously developed a numerical framework to model phase change thermal storage and have validated model predictions with experiments. The objectives of this paper are to describe the transfer of the numerical framework to an implementation in a Modelica component model and to validate the Modelica model with data from the experiment and the original numerical framework.

This study links a model of thermal energy storage (TES) performance to a subsystem model with heat exchangers that cool down the storage at night; this cool storage is used to precool the air flow for a power plant air-cooled condenser during peak day temperatures. The subsystem model is also computationally linked to a model of Rankine cycle power plant performance to predict additional power the plant could generate due to the additional cooling. The model was used to explore the effects of varying phase change material (PCM) melt temperature and the energy input and rejection control settings with the goal of maximizing efficiency for a 50 MW power plant operating in the desert regions of Nevada for an average summer day. The results suggest that the kWh output of the modeled plant can be increased by up to 3.25% during the heat input/cold extraction period, and a cost analysis estimates that the TES system has the potential to provide additional revenue of up to $686,000 per year, depending on electricity cost and parameter choices.

Although model predictions of thermal energy storage (TES) performance have been explored in several previous investigations, information that allows experimental validation of performance models has been very limited. This is particularly true for high-performance TES designs that facilitate fast input and extraction of energy. In this paper, we present a summary of performance tests of a high-performance TES unit using lithium nitrate trihydrate phase change material (PCM) as a storage medium. Our experimental program also included thorough property determinations and cyclic testing of the PCM. Performance data is presented for complete dual-mode cycles consisting of extraction (melting) followed by charging (freezing). These tests simulate the daylong cyclic operation of a TES unit for asynchronous cooling in a power plant. The model analysis is found to agree very well, within 10%, with the experimental data except for conditions very near the initiation of freezing. Slight deviation from the predicted performance at that time is a consequence of subcooling that is required to initiate solidification. The comparisons presented here demonstrate the viability of thermal energy storage for augmentation of power plant air-cooled condensers as well as other potential applications.

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.

Previous efforts to model the effectiveness of heat input and extraction from a thermal storage unit have generally been based on the definition of a constant conductance of heat from the working fluid to the phase change storage material. In order to capture the effects of changing thermal resistance between the working fluid and melt front location, this paper presents a method using a resistor network analogy to account for thermal conductance as a function of melt fraction. This expression for thermal conductance is then implemented in an existing numerical framework. Results are validated by comparing calculations for a single unit cell using a quasi-steady Stefan problem approach, a finite difference scheme, and more general form solutions from literature. The variable approach is then compared with an average value for overall thermal conductivity, U, to characterize the performance of a thermal energy storage unit consisting of a series of these unit cells. Overall effectiveness in the thermal energy storage device is found to be within 0.6% agreement when comparing these methods, though local percent deviation can be as high as 113%. Depending on the needed accuracy and use case for such a numerical framework, suggestions are provided on whether an average value for U is sufficient for characterizing such a thermal energy storage device. Discussion is also provided on the flexibility of the computation schemes described by testing the sensitivity of the results via changes in dimensionless input parameters.