Conference Agenda

The utilization of integrated heat pump thermal energy storage (HP-TES) systems for space conditioning applications can reduce electrical power demand and achieve utility savings resulting from peak shaving and load shifting. However, issues arise when the energy required to recharge the TES exceeds the shifted energy demand, especially in extreme climates where high-temperature lifts between the recharging outdoor air conditions and phase-change materials (PCMs) may occur. In this work, a single room-temperature (22°C) PCM-TES is integrated into a single-speed heat pump system using a secondary hydronic loop where the TES is recharged using the outdoor unit during off-peak hours. Three recharge strategies were investigated as potential pathways to reduce recharging power demand: (i) considering different heat source/sink temperatures, (ii) using a variable-speed compressor, and (iii) using a variable-speed pump. Simulations were conducted using Modelica for HP-TES recharging at different heat source/sink temperatures from -30 – 20℃ in heating mode and 0 – 30℃ in cooling mode. Results show that the most effective recharge demand reduction strategy is an HP-TES system using a single-speed compressor with a variable-speed pump for the hydronic loop run at preferable heat source/sink temperatures when the temperature lifts were reduced. Utilizing a variable-speed compressor for the HP-TES system reduced recharge time in extreme cases at the cost of additional compressor power input. The findings motivate potential control strategies that minimize recharge energy and maximize peak energy savings, hence reducing overall operating costs and annual energy consumption for HP-TES systems for space conditioning applications.

Electric heat pumps are a promising solution to decarbonize building heating by using renewable power and replacing existing fossil fuel based heating technologies. However, with the large-scale deployment of heat pumps, it is important to develop energy storage solutions to store renewable electricity and dispatch it when the generation is low, but the demand is high. This paper presents a system-level simulation of an air-to-water heat pump integrated with thermal energy storage for building heating. We coupled a validated quasi-steady thermodynamic model of the heat pump and a reduced-order transient model of a phase-change thermal storage module. We calculate the round-trip efficiency of the TES-integrated heat pump operating in the peak shaving mode using different TES materials for a representative commercial building. The performance of the proposed system showed a 26.67% reduction in the peak heating load in cold climates and the total electrical energy consumption for design day heating reduced by 4.8-11.5%. Our analyses show that a TES temperature close to the supply air conditions leads to a higher round-trip efficiency. Therefore, selecting a TES material based on its energy density (kJ/kg or kJ/m³), phase-change temperature, and cost is crucial to successfully implementing these systems. The configuration of TES-integrated heat pumps and the heat transfer design of the TES module will be essential to reduce the peak heating energy demand and emissions and help buildings interact with the future electricity grid with a high fraction of renewable power.

Energy storage at buildings can shift electric load to low-cost or low-emission periods, reducing the overall cost and environmental impact for operating buildings. This storage includes electric batteries, which directly shifts the metered load, and thermal energy storage, which shifts thermal-driven electric loads like air conditioning. While these are often seen as competing technologies, there can also be synergies between the two. In this paper, we discuss high-level advantages and disadvantages of thermal energy storage versus electrical batteries. We show how thermal storage coupled with an HVAC system often has a lower upfront cost than electric batteries—displacing electric batteries with thermal storage can reduce the initial $/kWh_e cost of a new storage system. We also show how batteries can be more flexible in their response to signals designed to limit a building’s peak demand. Using thermal storage with batteries can often lead to optimal solutions. Previous research has shown how this can reduce the cost of ownership, increase battery cycle life, and maximize the demand flexibility for different scenarios. In this work, we supplement this with experiments that combine a 30-ton chiller, a 160-tonh ice storage tank, and a 40-kWh electric battery. These are used together to reduce peak demand. We show how in the hybrid system, the chiller can operate at part load, at a high efficiency, reducing overall energy use, increasing the effective energy density of the thermal storage, and reducing its electric equivalent first cost. We also show how the efficiency of the HVAC&R equipment coupled to thermal storage, both the baseline equipment without storage and the equipment operating during discharge, has a strong impact on the electric equivalent first cost of thermal storage.

The grid-interactive heat pump (HP) system is designed to participate in demand response programs, thereby contributing to grid stability. Considering this, thermal energy storage (TES) incorporated with the grid-interactive HP has gained increasing attention due to its capacity for load shifting, energy cost reduction, and improved system flexibility. Efficient management of the TES charge and discharge processes, which is crucial for minimizing total energy costs, requires consideration of various factors such as electricity costs, weather data, and building cooling loads. Therefore, an intelligent control becomes essential for optimizing TES utilization in grid-interactive buildings. In this study, a dynamic model for controlling the TES-integrated HP system was developed and validated based on experimental data. A model predictive control (MPC) based on the dynamic programming method was then developed to optimize the performance of the HP-TES system, ensuring both reduced electrical costs and sustained human comfort. This optimal control was evaluated by comparing it with a rule-based control (RBC) through field tests in a real building. The results demonstrate that the proposed optimal control strategy exhibits intelligent system operation management by selecting different operation modes under various circumstances. Compared with RBC, it can achieve a 29% reduction in electric costs and a 10% decrease in energy consumption in a 3-day field test period. This paper provides insights into smart control for the grid-interactive HP system.

Thermal Energy Storage (TES) offers a promising solution for load shifting and reducing peak demand in buildings. The TES system under consideration in this paper is a hybrid rooftop unit (RTU) from Emerson with 5ton cooling capacity, integrated with a patented phase change material (PCM) from NETEnergy that functions as TES. The hybrid RTU system with PCM is currently in pre-commercialization stage, and offers important advantages over equivalent ice storage systems, namely significant reduction in added weight and cost, and a lot fewer moving parts and machinery. The hybrid RTU system with PCM has the potential to reduce peak demand by up to 40% and leverage time-of-use (TOU) utility rates to reduce operational costs for the customer. This paper provides the algorithm development, analysis, and results of implementing model predictive control (MPC) on the hybrid RTU with PCM using and high-fidelity physics-based models, and laboratory testing on actual equipment. The goal of the MPC is to maximize the benefits of the TES system with regards to load shifting, and peak demand reduction, while maintaining occupancy comfort.

The hybrid RTU consists of refrigeration and glycol circuits employed to charge and discharge the PCM, respectively. The charging circuit is coupled to the vapor compression system having R410-A as a refrigerant, while the discharging circuit uses an airstream to provide conditioned air to the thermal zone and discharges heat to the PCM through a water-glycol liquid coupling. Simple rule-based controllers (RBCs) fully charge the PCM during off-peak hours and discharge during the on-peak hours to reduce the on-peak compressor utilization, as this is the most energy intensive component of the system. This, however, leads to inefficient operation and higher utility costs, especially when the cooling demand is not very high. In this paper we design and test MPC to optimize the charging and discharging of the PCM to overcome the drawbacks of rule-based controllers. Reduced order models (ROMs) are developed for each component of the hybrid RTU and PCM, and mathematical optimization is performed to find the optimal charging/discharging trajectory of the PCM. MPC is then tested on high-fidelity physics-based models of the RTU and PCM components, followed by a laboratory demonstration quantifying the improvements over RBCs.