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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 37 records · Page 2

Thermally anisotropic building envelope for thermal management: finite element model calibration using field evaluation data

The thermally anisotropic building envelope (TABE) is an active building envelope that redistributes thermal loads in response to weather conditions and building energy demand. Conductive layers throughout the TABE distribute low-grade heat among hydronic loops, altering heat flow direction and intensity. Finite element models of TABE roof and wall panels were developed and calibrated using field evaluation data. The calibration results showed that heat flux differences between the experimental data and finite element models averaged –0.42% and 3.57%, with a maximum mean square error of 1.78 and 3.96 for roof and wall panels, respectively. A reduction in heat flux from the environment to the building living space over the entire testing period (weeks in July/August) was found to be 85% for roof panels and 335% (load reversed) for wall panels. Finally, these results indicate TABE can effectively harness low-grade thermal energy sources to achieve high energy efficiency and promote demand-side management.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI

Large-scale simulation-based parametric analysis of an optimal precooling strategy for demand flexibility in a commercial office building

Achieving success with grid-interactive efficient buildings (GEBs) is closely tied to the utilization of flexible loads. A valuable strategy involves the implementation of precooling techniques before high-demand events, such as peak hours, by adjusting zone air temperature setpoints. This leads to a reduction in thermal loads and peak electricity demand during these times, as the building’s thermal mass stores and subsequently releases thermal energy. However, the effectiveness of the pre-cooling optimization is highly contingent on specific conditions such as building thermal properties, weather conditions, utility rate structure, HVAC equipment sizing, etc. Therefore, investigating the impacts of these condition-specific factors is crucial, especially when considering precooling strategies that utilize thermal mass in commercial buildings. In this paper, we first devised a novel heuristic control approach that incorporates parameterized optimal precooling thermostat schedules to enhance demand flexibility in a commercial office building. Subsequently, we conducted a thorough performance evaluation of this control strategy. Here, the optimal thermostat schedule was parameterized using three optimization variables: the precooling start time, the precooling end time, and the precooling temperature setpoint. Utilizing the DOE medium-sized office building as the virtual testbed, we showed that the parameterized schedule effectively approximates model predictive control and requires drastically reduced computational overhead. In addition, we investigated the impact of different influencing factors on the optimal precooling strategy. These factors include building thermal mass, outdoor air conditions, and energy price profiles. Using high-performance computing, we simulated a total of 225 scenarios, consisting of three levels of thermal mass, five typical outdoor air temperature profiles, and fifteen time-of-use price plans. The results demonstrate that optimal thermostat scheduling could save substantial energy cost in medium-sized office buildings with heavy thermal mass but with some energy penalty. Although the potential for cost savings is lower in buildings with low and medium thermal mass, the energy penalty remains consistent in all three thermal mass scenarios. The study also highlights the need to account for zone diversity and recognize that a one-size-fits-all-zone setpoint schedule may not be suitable for all zones and can lead to unnecessary energy wastage. Furthermore, the results highlight that while outdoor air conditions play a role in cost and energy performance, the cooling load exerts a more immediate and substantial influence on cost savings in precooling strategies. Although cost savings are comparable under certain conditions with the same cooling load, observed deviations in energy penalty indicate potential disparities in the efficiency of the HVAC system during the load-shifting process. In addition, the duration of peak pricing and the ratio between peak and off-peak times exhibit clear correlations with cost savings and energy consumption, aligning with intuitive expectations. These findings offer valuable insights for optimizing precooling strategies in office buildings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI

CityLearn v2: energy-flexible, resilient, occupant-centric, and carbon-aware management of grid-interactive communities

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.

Nweye, Kingsley

Analytical workflow dependence of experimental observables for uranium chemistries

In this work, we investigated how the sequencing of laboratory analytical methods used for chemical and morphological characterization influences analytical findings for particulate materials relevant to the nuclear fuel cycle, including UO2, U3O8, studtite (UO2O2·4H2O), and β-UO3, in the context of nuclear forensic analysis. Particles of each chemistry obtained from consistent production batches were exposed to Raman spectroscopy and scanning electron microscopy in varying orders to elucidate how the order in which the techniques are applied influences morphological and chemical observations as a function of particle size. The results indicate that particles from all four chemistries exposed to high-resolution electron imaging before Raman spectral analysis demonstrate optical vibrational spectral changes that reduce accurate interpretation of the underlying chemistry via Raman spectral analysis. We hypothesize that these changes are due to the thermal load of the electron beam imparted to the sample being unable to be dissipated by materials with poor thermal conduction properties. Results from this study will aid in determining best practices for forensic analysis procedures to reduce uncertainty in chemical determination of unknown particulate samples.

Manns, Rebecca [University of Nevada, Las Vegas]

Validation and moisture content sensitivity analysis of cross-laminated timber wall assemblies in EnergyPlus

Cross-laminated timber buildings are becoming more common in North America, with many numerical studies showing potential energy savings. However, no studies have validated any EnergyPlus heat transfer algorithms or quantified their accuracy in simulating CLT in building envelopes. This study empirically validates the heat flux predictions for each of EnergyPlus's heat transfer algorithms (Conduction Transfer Functions (CTF), Effective Moisture Penetration Depth (EMPD), Conduction Finite Difference (CondFD), and Heat and Moisture Transfer (HAMT)) for two different CLT ply thicknesses with both summer and winter boundary conditions measured in controlled lab experiments. It also evaluates the model sensitivity of heat flux and heating and cooling loads to moisture content. The 1D validation shows that the HAMT model is the most accurate among all algorithms. All EnergyPlus's heat flux predictions are accurate independent of CLT plate thickness for summer conditions. However, the three constant property algorithms (CTF, EMPD, and CondFD) underpredict heat flux throughout the whole day during winter conditions. The 1D sensitivity analysis indicates that elevated moisture content can increase peak heat fluxes through the material by up to 20 %. Finally, the whole building model sensitivity analysis shows increased heating load and slight cooling load variation due to increased moisture content when using constant property models. The analysis shows significantly lower peak thermal demand (7 % lower heating and 6 % lower cooling) and monthly thermal load (8 % less cooling and 6 % less heating) predictions when using HAMT vs a constant property model.

42 ENGINEERING

Status and performance of the GlueX DIRC

In support of the future physics program at Ce+BAF, we propose a prototype positron target. The prototype target consists of a tungsten disk mounted on a water-cooled copper support structure to enhance heat removal. The primary goals of this work are to benchmark CFD simulations, ensure vacuum integrity at the 10^-6 Pa level, achieve stable target rotation up to 10 Hz, and implement efficient water-based cooling for sustained high-power operation. To manage the thermal load, the target is designed to rotate, allowing the deposited heat to spread over a larger region, and thereby reducing localized thermal stress while maintaining the maximum temperature below 1000 K. To experimentally evaluate the thermal performance and structural stability of the target, we plan to conduct high-power laser heating tests at Laser Lab 5, LERF Building, JLab. These tests will serve as a stepping-stone for the positron production target at CEBAF.

Stevens, J.R. [College of William and Mary, Willia

Cryogenic Gear System for ADMX Tuning Cavity

The Axion Dark Matter Experiment (ADMX) searches for axions by converting them into detectable photons using resonant microwave cavities at cryogenic temperatures. A precise tuning system is needed to adjust cavity frequency without adding thermal load or electromagnetic interference. This project developed and tested a 1000 to 1 gear reduction system made from PEEK, a low thermal conductivity plastic with good dimensional stability and self lubrication at low temperatures. A compound gear train design of five 3 to 1 stages and one 4 to 1 stage achieves high reduction within a 40 mm diameter compact housing. Prototypes were 3D printed and later CNC machined in PEEK using Fusion 360 and Bantam Tools to confirm manufacturability. Prototype testing showed smooth gear engagement and no slipping. The final gearbox improves cavity tuning precision for axion searches while protecting cryogenic conditions.

Ortega, Giancarlo [Marquette U.]

High-temperature seals for supercritical carbon-dioxide (sCO 2 ) turbines (Final Report)

This is the final report for project DE-FE0031924 titled “High-temperature seals for supercritical carbon-dioxide (sCO 2 ) turbines.” The report provides a summary of the entire project efforts from October 2020 through December 2024 including the high-temperature commercial dry gas seal (DGS) tests and thermal modeling of Task 2, as well as the high-temperature, large-diameter seal design and high-temperature tests of large-diameter seals in Task 3. A key outcome of Task 2 was the testing completion of specially instrumented commercial DGS in the GE-SwRI Apollo sCO 2 compressor (27,000 rpm). Test data from the DGS showed elevated temperatures upwards of 350 o F, which are close to the higher operating temperature limit of the DGS. The temperature measurements provide insight into the expected thermal loads on DGS operating in high-speed sCO 2 compressor and provided test data for validation of an in-house thermal model of the compressor/seal. Under Task 2.0, this report also presents the development of a steady-state conjugate heat-transfer model of the DGS operating in the sCO 2 compressor – a first of its kind model for modeling heat transfer of sCO 2 in an actual operating compressor. The findings of the thermal model show a reasonable match between temperature predictions of the model and the measured temperature data, also pointing out the validity of the approach and assumptions made in modeling the flows, heat transfer coefficients and windage modeling in the rig. Under Task 3.0, this report presents the preliminary design of a large-diameter hybrid face seal (14 inch and 26-inch diameter) for field testing in a land-based GE turbine. The preliminary seal design effort presented in this report under project DE-FE0031924 builds on the development and successful laboratory testing for such large diameter hybrid face seal under the prior DE-FE0024007 project. Key aspects of seal fluid analyses with CFD, mechanical design considerations and assembly considerations in a land-based turbine are presented. Finally, under Task 3.0, this report also presents the continued high-temperature testing of the 14-inch diameter hybrid face seal developed previously under the DE-FE0024007 program. Specifically, test data demonstrating successful non-contact seal operation and seal effective leakage of 0.001-inch with seal inlet temperatures above 700 o F are presented in this report. Successful hybrid seal operation in a laboratory environment for a large diameter (14-inch) seal at temperatures above 700 o F is a major technological milestone for this technology.

01 COAL, LIGNITE, AND PEAT

Understanding Electric Vehicle Range and Charging Needs: Interactions Between Ambient Temperature, Commute Patterns, and State-of-Charge Usage

Electric vehicle (EV) performance can vary substantially under real-world operating conditions, particularly due to ambient temperature effects on energy consumption, battery behavior, and thermal management requirements. This study quantifies how weather conditions, daily driving patterns, and State-of-Charge (SOC) usage strategies jointly influence EV driving range, charging frequency, and overall energy efficiency. A detailed and experimentally validated Autonomie vehicle model is developed, integrating a powertrain, a mono-zonal cabin model, and a battery electro-thermal model. Three battery sizes (200-, 300-, and 400-mile homologated ranges) are assessed across five commute profiles (20–200 miles) and six ambient temperatures (−18 °C to 50 °C), including scenarios with and without preconditioning. Results show that extreme temperatures could significantly decrease the maximum achievable range by up to 55% in cold conditions (−18 °C) and 40% in hot conditions (50 °C), relative to moderate conditions. Larger battery packs retain a greater fraction of their nominal range under thermal stress, while smaller packs experience sharper relative penalties due to the higher contribution of thermal loads to total energy demand. The analysis further demonstrates that limiting operation to partial SOC windows (e.g., 80–20%), a common real-world practice, significantly reduces achievable range and increases charging frequency, particularly in cold weather. Thermal preconditioning while plugged in is shown to mitigate these effects for short trips, reducing energy consumption by up to 31% in hot conditions and 7% in cold conditions. The findings demonstrate how climate, SOC usage behavior, and thermal management jointly shape the practical driving capability of EVs, highlighting the importance of efficient thermal management and realistic user charging strategies for ensuring reliable EV operation across diverse climatic scenarios.

33 ADVANCED PROPULSION SYSTEMS

Kinetics of Pyrolysis and Thermal Evolution of Negev Desert Lithologies

The Negev desert in Israel is home to large quantities of organic-rich, shallow marine sedimentary lithologies that could potentially accommodate the disposal of spent nuclear fuel. Previous thermal analyses of Negev carbonates have focused on industrially relevant considerations such as natural gas and oil extraction or pyrolysis for recovering hydrocarbon fuels. Here, this study addresses thermal evolution of the Negev organic-rich carbonate, siliceous, and phosphorite rocks and associated chemical, mineralogical, and microstructural changes that may occur under prolonged thermal loading in the vicinity of spent nuclear fuel disposal systems. Our employed methods include high-temperature X-ray diffraction, high-temperature infrared spectroscopy, and thermal analysis integrating thermogravimetry, differential scanning calorimetry, and mass spectrometry. Further, we apply iterative iso-conversional model-free methods to derive kinetic parameters for thermal decomposition of the Negev organic-rich carbonate rocks from 200 to 550 °C. Our results have provided mechanistic insights into the thermal evolution encompassing water desorption, decomposition of organic matter, and decarbonation of carbonate phases.

58 GEOSCIENCES

Disruption modelling for engineering and physics design of ST-E1 fusion power plant

Plasma disruptions represent a critical challenge for high-performance tokamak operations, as they can compromise machine integrity and reduce operational availability. Although future fusion devices essentially need to incorporate strategies to minimise disruption occurrence, complete avoidance remains unattainable. Consequently, assessing and characterising unmitigated disruption consequences is fundamental for the design and qualification of next-generation fusion power plants. This work supports the pre-conceptual design of ST-E1, a low aspect-ratio Tokamak Fusion Power Plant developed by Tokamak Energy Ltd., by presenting a comprehensive disruption modelling approach applied across different design stages. The methodology integrates both physics and engineering considerations to evaluate the impact of disruptions on machine performance and structural integrity. From an engineering perspective, several ST-E1 layout options were analysed to investigate the electromagnetic response of key components under disruption-induced loads, enabling comparison between alternative design solutions. On the physics side, a broad set of disruption scenarios was explored, scanning operational space parameters, plasma-material interactions, and associated thermal loads. Furthermore, the study examined variations in disruption behaviour arising from different reference equilibria, focusing on a range starting from Double Null to Single Null configurations, reflecting the increasing up-down asymmetry consequences. The results reveal significant contrasts in plasma dynamics and structures electromagnetic behaviour between configurations, highlighting the importance of disruption modelling in guiding design choices. These analyses have proven instrumental in shaping ST-E1 development, offering critical insights for mitigating risks and optimising future fusion power plant designs.

Borowiec, Katarzyna [ORNL] (ORCID:0000000335911739

Tailoring coherent beam combined laser pulse trains for high peak and average power applications

Laser systems based on coherent beam combination (CBC) that rely on tiled pupil architecture intrinsically carry digital capabilities independently applicable to all three essential characteristics of a laser pulse: amplitude, phase and polarization. Those capabilities allow the far-field energy distribution to be flexibly tailored in real time. Operation in the femtosecond regime at high repetition rates gives access to a wide range of applications requiring both high peak and average powers. We address the task of independent peak versus average power adjustment needed for applications seeking to decouple nonlinear phenomena associated with GW peak power from the thermal load inherent to kW average power operation. The technical solutions proposed are presented in the framework of the Ecole Polytechnique XCAN CBC laser platform (61 independent channels) with an emphasis on thermal management measures implemented to ensure its nominal operation.

47 OTHER INSTRUMENTATION

Cryogenic aspects of a 20 MW class low-temperature superconducting generator for the renewables industry

In this paper we give a progress update on the cryogenic design for cooling a 20 MW class, partially superconducting generator with stationary field coils for offshore wind renewables industry [1-2]. This is a continuation of an earlier program on a 10 MW system dating back ten years. Whereas this new power rating increase leads to a radial diameter expansion of the superconducting field coils from 4 to > 9.5 m, it maintains the axial length. We show the design based on this scaled up with enlarged diameter. The field coil size increase asks for higher cooling power that leads to a bigger cold box size to accommodate the cryocoolers. In the design, as many as 8 cryocoolers can be accessed and serviced from the nacelle that houses the main cryogenic components. A typical thermal load balance sheet with all components is given and compared against the available cryocooler cooling power at different operating conditions. Due to the cryocoolers’ local point of contact cooling within the nacelle, the temperature gradient of the thermal shield that fully encloses the cold mass with its embedded field coils needs to be balanced out to minimize the heat burden on the field coils. This requires additional analytical efforts and implementation of further design features. The extended nacelle houses the cold box with its cryogenic infrastructure. The interface for the envisaged cryogenic pushbutton closed-loop circulating system remains invisible, requires no handling of cryogenic liquids and is hermetically closed. The field coil diameter increase also leads to a greater initial helium gas storage volume. In addition, it requires higher initial room temperature fill pressure within the toroidal helium vapor storage tanks and in cooling tubes connecting to the cryocoolers. The toroidal helium gas tanks are thermally coupled with the thermal shield so that helium convection inside the storage tank can improve heat transfer and reduce the temperature gradient of the thermal shield. Besides those heat transfer challenges, additional mechanical strain within this large structure is exerted on the torque tubes during initial cooldown and when energizing field coils. Some of those design challenges are quite unexpected, leading to novel workarounds in order to maintain the chosen cooling strategy. Finally, we assess those design limitations in view of further cryogenic scalability with emphasis on manufacturability and assembly.

cryogenics

Holistic energy analysis method for thermal management architectures of data centers

Modern high-performance computing (HPC) data centers (DCs), particularly those supporting energy-intensive artificial intelligence (AI) workloads, face escalating thermal management challenges that degrade performance through thermal throttling and drive up cooling power consumption and operational costs. To address this challenge, many have developed a wide variety of thermal management solutions (single-phase, two-phase, direct, indirect, hybrid, and more) which attempt to cool HPC DCs effectively while attempting to minimize overall system power consumption. However, the analysis of these solutions and methods to effectively compare one with another is lacking. Overall power usage effectiveness (PUE) and total-power usage effectiveness (TUE) provide a metric to quantify power consumption but fail to identify components in the system which require further optimization. To address this, we propose a holistic analytical framework – the waterfall diagram (WFD) – which leverages a waterfall chart methodology, offering a comprehensive visualization of both the thermal management system loop and heat flow pathways from individual server components to the outdoor ambient. Use of the WFD enables graphical estimations of power efficiency and cooling performance across each component of a DC cooling system and complements Sankey-style energy flow visualizations by additionally resolving stage-wise temperature changes and incremental TUE contributions. The framework is used in conjunction with simulation-based approaches, to conduct a detailed pressure drop and flow distribution analysis aimed at identifying the optimal coolant distribution architecture for a single-phase direct-to-chip water-cooled DC, which serves as the baseline for subsequent WFD analysis. Among the evaluated architectures, the 3 U modular coolant distribution architecture is found to demonstrate the best performance, considering minimal pressure drop and uniform flow distribution. In addition, TUE is calculated for each cooling loop component based on its associated pressure drop and corresponding pumping power, which are integrated into the WFD. This correlation between TUE and local temperature offers immediate insight into the power efficiency and thermal performance contributions of individual components, facilitating further development and optimization. Examples of WFD applications are presented under varying thermal loads and ambient conditions, demonstrating reasonable cooling strategies. Notably, the 3 U modular architecture maintains a consistent chip case temperature of 85°C, achieving a TUE of 1.016 at ambient temperature of 47°C, and a TUE of 1.026 at ambient temperature of 52°C. The WFD methodology provides an efficient, holistic, and streamlined framework for DC thermal management architecture assessment and enables design optimization which is important for addressing the thermal-fluidic energy challenges of current and next-generation DCs.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI

First Solar Thermal Energy Planner (STEP 1) and Nationwide Industrial Heat and Power Analysis

The First Solar Thermal Energy Planner (STEP 1) and Nationwide Industrial Heat and Power Analysis (aka the STEP 1 Project or the Project) aimed to (1) developed a brand-new web tool that could provide decision support through free, rapid techno-economic analysis of behind-the-meter solar+storage systems for industrial process heat and (2) conduct high-level analyses of the cost-competitiveness of the same systems across the US in key sectors. The STEP 1 web tool collects key location, land availability, thermal load profile, proccess heat temperature and media, and other key parameters through an easy-to-use user interface (UI). The UI was designed to meet the user at their level of understanding by minimizing the number of required inputs as much as possible while including options for more nuanced inputs if the user desires. STEP 1 advises users on which solar thermal tehcnologies that could fit their needs based on the inputs provided (namely process media and temperature). The tool can model a wide range of solar thermal technologies including flat plate collectors, evacuated tubes, parabolic troughs, linear Fresnel, and molten salt towers all with corresponding thermal energy storage (TES) - solar PV with resistive heating and TES is also included. Once the parameters are collected, a nominal thermal energy production profile for the facility's location is generated using NREL's System Advisory Model (SAM) and then passed to a modified version of NREL's REopt platform to optimize the size (capacity) and dispatch of the solar+storage system to minimize lifecycle costs subject to energy balance, fuel and electricity rates, emission reductions goals, and other constraints. This entire process takes less than 20 minutes, is completely free, requires zero coding skills, and provides the user with a high-level assessment on the techno-economic feasability of deploying solar+storage systems for their energy needs. In addition to the development of the STEP 1 web tool, the project completed two complementary analyses focused on leveraging the backend code of STEP 1, public industrial facility locations and fuel consumption data, and key sector information to assess the economic opportunity of reducing fuel costs at various levels of capacity factor around the US. Both analyses found that there are key markets, locations, industrial sectors (namely food and beverage), and degrees of offset where solar thermal technologies could be cost-effectively deployed, highlighting a key market entry point for these technologies, and assessing deployment potential. In summary, the STEP 1 project improved the opportunities for solar+storage systems to expand into the industrial process heat market through breaking down barriers to assessing these technologies.

14 SOLAR ENERGY

Estimation of intensity, footprint, and capacity of surface urban heat islands using a direction-enhanced adaptive synchronous extraction (DEASE) method

Here, the surface urban heat island (SUHI) effect, assessed through remotely sensed land surface temperature (LST), remains a focal point in urban climate research. Conventional indicators like SUHI intensity (SUHII) and footprint (SUHIF) capture peak values and spatial extent but fail to account for the cumulative thermal load—a critical dimension reflecting the total heat exposure imposed by spatially continuous warming, which directly limits a holistic assessment of ecological and societal impacts of the SUHI effect. Therefore, this study introduces an indicator termed SUHI capacity (SUHIC), designed to quantify the aggregated SUHI effect by integrating the magnitude of the warming signal across all affected areas, thereby enabling a more comprehensive evaluation of urban thermal environments. Furthermore, a direction-enhanced adaptive synchronous extraction (DEASE) method is proposed for the quantification of SUHIC. This method can dynamically identify the optimal background reference area based on the urban-rural LST gradients in various directions within the city, without relying on predefined mathematical models as previously. The results from 102 European cities first confirm that the directional variations in urban-rural LST gradients, and the DEASE method can effectively capture these distinctions for the simultaneous estimation of SUHII, SUHIF, and SUHIC. Secondly, the spatial patterns of absolute SUHIC values show strong associations with those of SUHIF (R2>0.86), while its relative values (normalized by the area of urban) align more closely with SUHII (R2 > 0.64). More importantly, SUHIC can serve as a crucial reference for assessing the urban thermal signal when SUHII and SUHIF diverge. The proposed method and framework contribute to standardizing the quantification of the SUHI effect.

Indicator

DEVAP-EDDR-TES (Simulation framework for a desiccant assisted air conditioning system with heat pump regeneration and energy storage) [SWR-24-66]

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.

Huang, Ransisi

Energy Saving Estimation of ASHRAE Guideline 36 Supervisory Setpoint Reset Controls in a Commercial Large Office Building

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.

ASHRAE Guideline 36, Commercial buildings, Control