Theoretical Minimum Thermal Load in Buildings
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Economic and population growth is leading to increased energy demand across all sectors—buildings, transportation, and industry. Adoption of new energy consumers such as electric vehicles could further increase this growth. Sensible utilization of clean renewable energy resources is necessary to sustain this growth. Thermal needs in a building pose a significant challenge to the energy infrastructure. Potential technological solutions to address growing energy demand while simultaneously lowering the carbon footprint and enhancing the grid flexibility are presented in this study. Performance assessment of heat pumps, solar thermal collectors, nonfossil fuel-based cogeneration systems, and their hybrid configurations is reported in this study. The impact of design configuration, coefficient of performance (COP), electric grid’s primary energy efficiency on the key attributes of total carbon footprint, life cycle costs, operational energy savings, and site-specific primary energy efficiency are analyzed and discussed in detail. In conclusion, heat pumps and hydrogen-fueled solid oxide fuel cells (SOFCs) are highly effective building energy resources compared to traditional approaches; however, the carbon intensity of electrical energy and hydrogen production are keys to the overall environmental benefit.
In accordance with the developing economy and growing population, an increasing number of tall buildings have been constructed over the last 20 years. In 2017, there were 144 new buildings worldwide that were 200 m or greater in height; 50% of these buildings were in China. Due to the vertical gradient impact of meteorological parameters, the energy performance of tall buildings differs from that of general buildings. Few studies exist on vertical meteorological changes using measured data at different heights. Most studies on dynamic energy simulation simulate meteorological parameters using models. This study explores vertical meteorological patterns using hourly dry-bulb temperature, relative humidity, and wind speed data from 2007 to 2017 for a 325 m meteorological tower in Beijing. The temperature decreased significantly with increasing altitude (~0.9 °C per 100 m), while the daily temperature difference decreased with increasing altitude. The absolute humidity did not change significantly with height. The wind speed increased with altitude at approximately 2 m/s per 100 m. The building simulation showed that the annual heating load at a height of 320 m increased by 85% from that at 8 m; the annual cooling load decreased by 20%. Such significant differences in thermal loads for 300-m-tall buildings confirm the need to consider vertical meteorological differences in building performance simulations for tall buildings. A greater number of measurement points at different heights improve the simulation accuracy. Finally, guidance on selecting the heights for vertical metrological measurements is provided based on the influences of building thermal loads.
Precooling is a recognized technique for reducing cooling energy in buildings during peak hours by shifting load to off-peak hours. This technique is particularly effective in buildings with high thermal mass, because of their large thermal energy storage capacity, and in commercial buildings due to their variable electricity pricing based on time-of-use rates. Precooling in residential buildings has been a matter of limited interest in the past because of their low thermal mass and typically uniform electricity pricing rate. While previous studies on precooling primarily focused on cost savings, an important aspect of precooling is the thermal load modulation, which could be very effective in managing peak demand in lightweight residential buildings integrated with thermal energy storage systems. In this study, we examine different precooling strategies to manage the heat gains in lightweight building walls integrated with phase-change materials. We create nine different precooling profiles by controlling the interior temperature, and then evaluate the influence of the precooling profiles on four key building energy performance parameters: total heat gain, peak heat gain, maximum heat gain during peak hours, and time at which peak occurs. To thoroughly understand the fundamental physics, we first consider hypothetical climates and obtain the optimal precooling strategy required to achieve maximum peak shedding and shifting while minimizing the total heat gains. We then extend the model to Baltimore, Maryland, and estimate the benefits of the optimized precooling strategy under real conditions. The optimal precooling strategy proposed in this study can shift the peak heat gain by up to 14 hours, thereby reducing the heat gain during peak period by up to 95%, at the expense of a 23% increase in the total heat gains.
As more distributed energy resources become part of the demand-side infrastructure, quantifying their energy flexibility on a community scale is crucial. CityLearn v1 provided an environment for benchmarking control algorithms. However, there is no standardized environment utilizing realistic building-stock datasets for distributed energy resource control benchmarking without co-simulation or third-party frameworks. CityLearn v2 extends CityLearn v1 by providing a stand-alone simulation environment that leverages the End-Use Load Profiles for the U.S. Building Stock dataset to create grid-interactive communities for resilient, multi-agent, and objective control of distributed energy resources with dynamic occupant feedback. While the v1 environment used pre-simulated building thermal loads, the v2 environment uses data-driven thermal dynamics and eliminates the need for co-simulation with building energy performance software. This work details the v2 environment and provides application examples that use reinforcement learning control to manage battery energy storage system, vehicle-to-grid control, and thermal comfort during heat pump power modulation.
Replacing carbon-intensive fossil fuel heating systems with electric heat pumps powered by renewables is a promising approach to decarbonize the building sector. However, one of the technical barriers of this approach is the large scale of heat demand, which will put excessive stress on the electricity grid. Integrating thermal energy storage (TES) into the heating systems can help alleviate this problem, by shifting thermal load and thus shaving peaks in the building electric load. Therefore, it is critical to understand how to design a thermal storage device in a heat pump for peak load shaving. In this study, we developed a numerical model for a cascaded vapor compression heat pump system integrating a phase change thermal storage device. This novel system can control the net thermal charging and discharging rate of the TES independently from the building's thermal load, which allows for precise control of electric power use. In the current study, we controlled the system to shave building electric peak load during a cold winter morning, and to charge TES during the relatively warm afternoon while still providing space heating. We used the model to evaluate the system performance with and without peak shaving. We also investigated the effect of PCM transition Tt on the peak reduction and electric energy saving potentials. The results show that peak shaving scheme effectively reduces the peak electric power consumption during a predefined discharge time window. When comparing to the no shaving case, for PCM Tt = 10 degrees C, the peak electric load reduction is 23.5%. When comparing to an air-source heat pump with back up electric heater, as Tt increases from 0 to 20 degrees C, the peak reduction increases from 46.1% to 50.9%. Integrating PCM Tt = 10 degrees C with peak shaving leads to the 45.5% of electric energy saving, which is the highest among the three transition temperatures.
Phase change material (PCM)-based thermal energy storage (TES) can provide energy and cost savings and peak demand reduction benefits for grid-interactive residential buildings. Researchers established that these benefits vary greatly depending on the PCM phase change temperature (PCT), total TES storage capacity, system configuration and location and climate of the building. In this study, preliminary techno-economic performance is reported for a novel heat pump (HP)-integrated TES system using an idealized approach. A simplified HP-TES was modeled for 1 year of space heating and cooling loads for a residential building in three different climates in the United States. The vapor compression system of the HP was modified to integrate with TES, and all heat transfer to and from the TES was mediated by the HP. A single PCM was used for heating and cooling, and the PCT and TES capacity were varied to observe their effects on the building’s energy consumption, peak load shifting and cost savings. The maximum reduction in electric consumption, utility cost and peak electric demand were achieved at a PCT of 30 °C for New York City and 20 °C for Houston and Birmingham. Peak energy consumption in Houston, New York City, and Birmingham was reduced by 47%, 53%, and 70%, respectively, by shifting peak load using a time-of-use utility schedule. TES with 170 MJ storage capacity allowed for maximum demand shift from on-peak to off-peak hours, with diminishing returns once the TES capacity equaled the daily building thermal loads experienced during the most extreme ambient conditions.
Thermal energy storage (TES) can alleviate peak demand on the electricity grid by offsetting building thermal loads, increasing the grid’s reliability and resilience. However, low energy density and poor energy performance of existing TES technologies limit their applications. Sorption-based thermal battery (STB) system is thus developed using three-phase sorption technology to harvest low-temperature heat, store it with a much higher energy density than common TES systems and dehumidify air or provide space cooling in buildings. Although STB has been experimentally proved to be feasible, influencing factors on its performance are still unknown by far. Therefore, this paper conducted a parametric analysis on crystallization and crystal dissolution performance of a developed STB test rig. The crystallization results showed that the energy density of the STB increased with reducing the solution flow rate and the cooling water temperature. The dissolution results showed that a higher discharge rate of the STB can be achieved with increasing the flow rate and temperature of inlet diluted solution. The work in this study is helpful to the optimal design and operation of the STB system.
Phase-change material (PCM) thermal-energy storage (TES) integrated with HVAC and domestic hot water (DHW) can shift a large share of building thermal loads. By flattening and shifting loads, PCM TES reduces peak electricity use, eases stress on local and grid infrastructure, and lowers costs. It can also defer costly upgrades to service panels, distribution, and transmission. Higher energy density relative to chilled or hot water storage makes PCM TES practical for small, space limited, and retrofit projects, while packaged HVAC-integrated systems expand cost-effective load shifting to commercial buildings that previously lacked options. Despite this promise, deployment faces barriers. This paper presents challenges, opportunities, and lessons learned from lab and field integrations of PCM TES with packaged HVAC systems. Key challenges include misalignment between default heat pump controls tuned for direct-to-load operation and TES charge/discharge objectives, PCM properties that diverge from manufacturer claims and evolve with cycling, and high integration and deployment costs with off-the-shelf products. These studies underscore the need for factory built, integrated systems that arrive as prepackaged modules with proven controls, reducing design and installation effort and delivering predictable performance across projects. The paper outlines steps to enable viable and scalable PCM TES HVAC and DHW systems, including 1) validated methods that can be used to characterize PCM properties and TES system performance, 2) supervisory controls that optimize charge/discharge scheduling, and 3) factory integrated packaging that eliminates bespoke field engineering.
This software is a simulation framework that models a load flexible air conditioner system. The system consists of an evaporatively cooled liquid desiccant air conditioner (eLD-AC) subsystem, an electrically driven desiccant regenerator (EDDR) subsystem, and a stratified liquid desiccant storage (SLDS) subsystem. The software can be used to 1) predict the steady-state performance of the system given user-specified convergence criteria; 2) predict the dynamic performance of the entire system over a typical drive cycle operation subjected to user-specified building thermal loads and desired electrical load profile; 3) evaluate the synergy of all three subsystems operating altogether and improve the energy storage control strategy.
Designing, commissioning, and retrofitting HVAC control systems for energy efficiency is crucial, but the use of ad-hoc control sequences by designers and contractors, based on scattered information, results in diverse and sub-optimal sequences. ASHRAE Guideline 36 (G36) addresses the challenge by providing standardized, rule-based HVAC control sequences that prioritize energy efficiency. However, there is limited evaluation of their energy performance at the building level, with only a few studies primarily focused on HVAC airside systems in small-to-medium-sized commercial buildings. In this study, the energy performance of ASHRAE Guideline 36 control sequences was assessed using a large office building emulator in Chicago. The emulator features a central plant system with multiple chillers and boilers as well as multiple variable air volume (VAV) systems with terminal reheat. To achieve a high-fidelity representation, we developed a Spawn-of-EnergyPlus-based model for the large office building, maintaining the DOE prototype large office building setup but substituting the HVAC system with its Modelica counterpart. This substitution ensures that the building thermal load, HVAC system's dynamics, and detailed control sequences are all accurately represented. The study involved evaluating and implementing control strategies outlined in ASHRAE Guideline 36-2021 to replace conventional controls. These strategies include the demand-based supply air temperature and duct static pressure setpoint reset and the request logic for demand-based reset of chilled/hot water supply temperature setpoints and pipe static pressure setpoints. Energy performance was evaluated under various load conditions, including cooling, heating, and transitional seasons, both for individual control strategies and in combination. The results indicate that the collective control strategies retrofit yield greater energy savings than the sum of individual strategies, highlighting the synergistic benefits of incorporating both airside and plant-side control retrofits. Additionally, energy savings of up to 41% in the heating season, 18% in the shoulder season, and 20 % in the cooling season were observed compared to baseline control while maintaining the thermal comfort level.
Combi heat pump systems, also referred to multifunctional variable refrigerant flow heat recovery (MF-VRFHR) systems, are specifically designed for residential applications to manage both space conditioning and domestic hot water (DHW). They have attracted attention due to their potential for energy conservation through heat recovery. The incorporation of a hot water tank introduces various system configurations, each characterized by distinct pros and cons related to energy efficiency, system stability, and maintenance. Despite this, a critical gap exists as the specific energy performance remains unquantified under diverse operational modes (e.g., heating mode and heat recovery mode). This paper aims to bridge this gap by conducting a comprehensive comparative analysis of two prevalent system configurations while considering feasible proposed control logics. Configuration 1 integrates a separate hot water tank and a refrigerant-to-water heat exchanger (HEX), also known as a Hydro Kit while Configuration 2 incorporates a refrigerant-wrapped hot water tank. To facilitate this analysis, we developed high-fidelity system models for both configurations in Modelica, capturing system dynamics and detailed control sequences effectively. These system models were built upon the TIL library for HVAC equipment components and the Buildings library for residential building thermal load calculations. The validation of the simulation testbed utilized data from experiments conducted in the PNNL lab home for Configuration 1. To establish the simulation testbed for Configuration 2, we extended the modeling setup derived from Configuration 1. This extension specifically involved substituting the separate hot water tank and Hydro Kit with a refrigerant-wrapped hot water tank of similar sizing sourced from an actual product. The simulation analysis of heating-only and heat recovery modes reveals that Configuration 2 not only saves energy and maintains warmer tank temperatures but also demonstrates faster water heating capabilities. This is attributed to decreased energy loss and improved heat transfer. The study encompasses a wide range of scenarios, considering diverse thermal loads and water usage patterns across heating and heat recovery modes. Overall, the comprehensive results indicate that Configuration 2 achieves energy savings ranging from 3.5% to 12.2% compared to Configuration 1, depending on factors such as water usage patterns, thermal loads, and operational modes.
The relative value of thermal energy storage (TES) for heat pump storage (heating and cooling) as a function of storage temperature, mode of storage (hotside or coldside), geographic locations, and utility time of use rate structures were derived. Computer models used to simulate the performance of a number of TES/heat pump configurations are described. The models are based on existing performance data of heat pump components, available building thermal load computational procedures, and generalized TES subsystem design. Life cycle costs computed for each site, configuration, and rate structure are discussed.
Load modulation in buildings is becoming increasingly important due to growing disparity in energy demand during peak and off-peak hours. Integrating phase change material (PCM) in building envelopes and using a controlled precooling strategy can provide substantial thermal load modulation; however, it may greatly increase the total energy use. Previous studies have employed PCM in building envelopes primarily for energy savings and, to some extent, peak load shedding and shifting. However, the load modulation capacity of a PCM-integrated envelope has not been well explored in the literature. In this study, we perform an extensive parametric and sensitivity analysis on PCM-integrated lightweight building walls and examine the combinatory effects of various PCM parameters on thermal load modulation and wall-related heat gains in buildings. Using numerical simulations, we investigate eight PCM parameters: PCM location in the wall, transition temperature, thickness, latent heat, transition range, density, specific heat, and thermal conductivity. Here, we evaluate their impact and relative importance to achieve maximum load modulation in buildings without compromising occupants’ thermal comfort or total energy use. The results show that the optimized PCM proposed in this study can completely invert the transient heat gain profile of the wall, providing up to 70% reduction of wall-related heat gain during peak hours without a major increase in the cumulative heat gain.
Grey-box modeling, as one of the three fundamental modeling techniques for building energy models, has many advantages compared with black-box modeling and white-box modeling. Additionally, it has been widely applied to solve problems of building technologies, such as building load estimation, control and optimization, and building-grid integration. However, a thorough review of grey-box modeling is not available. This review study systematically investigated various aspects of grey-box modeling for buildings. First, the fundamental aspects of grey-box modeling are presented, including the theoretical background, modeling of building elements, modeling order, modeling diagram, and order reduction. Second, the detailed modeling approaches are discussed. Third, multiple applications of grey-box modeling are investigated for building energy domain, which are categorized into the following groups: heat dynamics analysis, thermal load estimation, building control and optimization, district/urban scale energy modeling, and building-grid integration. Finally, the available software packages for grey-box modeling are compared. Overall, the challenges of using grey-box modeling can be summarized as follows: (1) the theoretical limitations and assumptions of grey-box modeling are unclear; (2) grey-box model naming convention and structure are confusing; (3) grey-box model creation is vague; (4) suitable applications of grey-box models are unknown; and (5) grey-box models lack unified software solutions for wider adoption.
To support the U.S. Department of Energy's (DOE's) Advanced Building Construction (ABC) Collaborative, the National Renewable Energy Laboratory (NREL) has been tasked with characterizing the U.S. building stock and developing a national typology of buildings. The potential use cases of such a typology are flexible and evolving, but in this initial phase, the primary intention is to help identify technology requirements and engineering solutions for moving the U.S. building stock toward a zero-carbon future by mid-century. This typology will also support the development of appropriate ABC research goals for existing buildings, such as cost targets for new technology development, and in a later phase, the typology can be used to support the implementation of ABC solutions by informing market aggregation and business model development. The ABC Initiative invests in new technologies that enable high building performance, can be deployed quickly with minimal onsite construction time, and are affordable and appealing to building owners, investors, and occupants. Funding awardees use many innovations, including new building materials, 3D printing, offsite manufacturing, robotics, and digital art-to-part. Although the goals of ABC cover a broad range of objectives around energy, comfort, and health, the primary ABC-related application of this national building characterization study is the development of retrofit packages that can be applied to reduce thermal loads in buildings. Retrofit packages will be determined collaboratively by the DOE and the ABC Collaborative. We anticipate a range of upgrade measures covering envelope-, HVAC-, and water-heating-related loads.
The building envelope has traditionally been seen as a static component. Much of the past thermal advancements in building envelopes has consisted of developing higher R/inch insulation. While a suitable approach for static situations, it does not consider the dynamic nature of the ambient environment or the varying needs of the electrical grid. This paper will examine three possible ways that building envelopes can be actively managed: 1. thermal switches, 2. thermal storage, and 3. the coupling of the two. Spurring innovation to make building envelopes smarter will help reduce building energy consumption and peak energy usage and contribute to flexibility in energy demand in the future.
While there is considerable focus on latent-based thermal energy storage (TES) systems, the low thermal conductivity of phase change materials (PCMs) remains a critical concern. Many approaches to enhance PCM conductivity either require complicated synthesis processes or are cost prohibitive. In this study, we investigate finned-tube modular TES systems, which are simple in design, easy to manufacture, and cost-effective due to their standard materials and components. The study includes detailed modeling and experimentation of two devices containing similar amounts of PCM but different fin spacings. The study reveals that having more fins does not necessarily increase the TES thermal performance because the reduction in the PCM volume fraction can reduce the TES volumetric and specific energy densities. We find that larger fin spacings provide a higher specific energy for lower C rates (<1C), while smaller fin spacings provide a higher specific energy for higher C rates (>1C).