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At least 37 records · Page 2

Evaluation of HVAC & refrigeration system fault behaviors and impacts: A systematic review

Achieving the goals of green buildings critically depends on the fault-free operation of heating, ventilation and air conditioning and refrigeration (HVAC&R) systems. However, faults frequently occur in these systems, causing a range of negative consequences, including increased energy consumption, diminished operational performance, compromised indoor environmental quality, higher operational costs, and shortened system lifespan. The evaluation of fault behaviors and impacts plays a critical role in revealing fault characteristics and consequently supports many research areas, including the design of the high-performance equipment, development of fault detection and diagnostics (FDD) and robust control approaches, as well as the enhancement of maintenance decision-making activities. This paper systematically reviews 112 research publications that reported the analysis and evaluation of fault behaviors and impacts in HVAC&R systems over the past thirty years. Here, we designed a review approach to address five crucial research questions, namely: 1) the objectives of analysis and evaluation of fault behaviors and impacts, 2) data sources, 3) equipment/system types and fault types, 4) evaluation methods including evaluation measures and associated metrics, and 5) challenges and future directions in the research on evaluating of fault behaviors and impacts. In-depth discussions on these questions help bridge the gap between the evaluation of fault behaviors and impacts and their practical applications, such as the development of high-performance systems, fault models, FDD methods, and maintenance decision-making tools within the HVAC&R FDD domain.

Chen, Yimin [Oak Ridge National Laboratory (ORNL),

Online Dynamic Mode Decomposition Based System Identification of Multi-Zone Building HVAC Systems

Many works have recently been conducted to reduce the electricity consumption of smart buildings and allow them to support various grid services. Most of these works require accurate system models for the various appliances in the building including heating, ventilation, and air conditioning (HVAC) units. In this paper, we investigate a recursive data-driven system identification strategy to construct the thermal model for a time-varying building with a multi-zone HVAC unit. The online dynamic mode decomposition (DMD)-based strategy is employed to identify the multi-zone thermal building dynamics, where a simple information update (rank-1) is selected to avoid computational complexity. The DMD-based identification strategy is validated using a real gymnasium building equipped with a 4-zone HVAC unit, and its performance is compared with that of the traditional nuclear-norm subspace identification (N2SID) strategy.

Wu, Tumin [University of Tennessee, Knoxville (UTK

Impact of refrigerant undercharge faults on building indoor conditions and HVAC system operation in residential Buildings: A simulation study

This study investigates the impact of refrigerant undercharge on indoor temperature and HVAC system performance in residential buildings. Simulation models for typical residential buildings in Orlando, FL and Indianapolis, IN were developed using the ResStock database. A refrigerant undercharge fault model was then applied to the simulations with varying levels of fault intensity. The paper offers an extensive analysis, revealing that variations in supply air temperature, equipment runtime, and cooling energy consumption due to the level of refrigerant undercharge faults are notably significant on a summer representative day. Similarly, on a winter representative day, changes in supply air temperature and runtime are significant as well as changes in supplemental heat energy consumption. We find that occupants may remain oblivious to these faults during the cooling season, particularly when the HVAC system is oversized; in that case, supply air temperature data could help detect a fault. Another challenge is that during the heating season, when the supplemental heater operates, it is difficult to identify a refrigerant undercharge fault using only indoor and supply air temperature data. Finally, this study finds that supply air temperature, equipment runtime, and supplemental heater energy consumption data can help in detecting refrigerant undercharge faults.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI

Smart building HVAC control challenge: experience and solutions from the ADRENALIN project

A smart building HVAC control competition crowdsourced and compared algorithms on fair and equal ground using the standardized BOPTEST framework. The competition attracted 138 participants, but only 9% submitted valid solutions for the final stage, highlighting the complexity of advanced HVAC control design. The winning solutions showed significant potential to reduce energy use and cost by shifting demand, without compromising occupant comfort. Across scenarios, thermal energy cost reductions of 36–76% relative to a baseline, were achieved. In peak heat periods, the cost reduction leveraged limited energy use reduction (0–15%), but more significant energy price reduction (34–62%). This shows smart controls' ability to avoid as much as possible consumption during the morning peak hours, when spot prices are tendentially the highest. Hosting the competition has highlighted challenges in creating competitions that both are fair and promotes solutions that are transferable to real life implementation.

BOPTEST

Optimizing Control for Efficient Load Shifting with Thermal Energy Storage in Existing HVAC Systems

This project developed the integration of a direct-contact heat exchanger (DCHX) based thermal energy storage (TES) system with a chiller–air handling unit (AHU) plant to evaluate its potential for reducing building energy costs. Detailed physical models of the TES unit, building envelope, and HVAC components were developed alongside simplified control-oriented models to support both high-fidelity simulation and real-time optimization. Two control strategies were implemented and compared: a rule-based control (RBC) aligned with utility time-of-use (ToU) rates, and a model predictive control (MPC) framework leveraging forecasts of building load, weather, and internal gains.Simulation results show that the RBC strategy reduced daily electricity costs by around 30% by shifting cooling production from on-peak to off-peak hours. In contrast, the MPC strategy achieved significantly greater performance, reducing daily operating costs by up to 44% and peak-hour costs by more than 60%. Both strategies maintained indoor thermal comfort within acceptable limits, with MPC further improving load distribution and reducing equipment cycling.The outcomes confirm that TES integration, particularly when coordinated with advanced predictive control, can provide substantial cost savings and on-peak demand reduction. . These findings directly support the U.S. Department of Energy’s goals for grid-interactive efficient buildings and demonstrate the potential of TES-enabled HVAC systems for scalable deployment across the commercial building.

99 GENERAL AND MISCELLANEOUS

Commercial building HVAC demand flexibility with model predictive control: Field demonstration and literature insights

Model Predictive Control (MPC) for building Heating Ventilation and Air Conditioning (HVAC) systems is beginning to gain traction in the market, with a few controls companies incorporating it into their product offerings. However, it remains difficult to assess whether the energy cost savings are enough to justify the cost of MPC implementation for a particular building, given the limited number of reported demonstrations. For small commercial and residential buildings with relatively uniform systems, standardized approaches can help lower implementation costs. In contrast, for large buildings or district systems, the potential magnitude of cost savings could justify more customized solutions. Estimating the cost-effectiveness of MPC becomes more challenging for medium and large commercial buildings, where a one-size-fits-all solution may not be suitable, and the potential energy cost savings may be insufficient to justify a customized solution. To make MPC technology more appealing, incorporating additional value streams beyond energy efficiency alone can significantly increase its attractiveness. One such revenue stream is demand flexibility, in response to dynamic electricity prices, where MPC can leverage the thermal mass of the building to shift the load and support the grid. Building on an extensive literature review of MPC field studies focused on cost savings and demand flexibility, this paper presents the results of implementing MPC control in a large office building HVAC system in Berkeley, CA. Four different dynamic electricity price profiles were integrated into the MPC objective function to shift building demand while maintaining comfort, and field testing was performed with each price profile across four seasons. The results show potential for 40–65 % demand decrease percentage and up to 61 % annual cost savings compared to the existing rule-based control strategy, under the tested dynamic price scenarios. This paper also presents a sensitivity analysis on the cost savings with respect to the price profile variability, discusses the implementation effort for the price-responsive MPC, and compares the cost savings found in this study to those found in literature on the basis of dynamic price variability, or so-called Electricity Price Relative Standard Deviation.

Zanetti, Ettore

Field-based AFDD for refrigerant undercharge in residential HVAC systems: enhancing reliability through false alarm mitigation

This study evaluated rule-based and machine learning (ML) based automated fault detection and diagnostics (AFDD) algorithms for detecting refrigerant undercharge faults in residential heating, ventilation, and air conditioning (HVAC) systems, using actual building data and a minimal set of features. The ML-based algorithms included Decision Tree (DT) and K-Nearest Neighbors (KNN). Both the rule-based and ML-based algorithms demonstrated the capability to detect refrigerant undercharge faults of -30% or more. Both types of algorithms exhibited false alarms before the implementation of a false alarm mitigation algorithm, which motivated the development of such a mitigation strategy. After applying the mitigation, false alarms were substantially reduced, with the rule-based algorithm decreasing to 0.6% and the ML-based algorithms reaching 0%, while maintaining strong detection performance. Although the rule-based algorithm initially showed lower performance compared to the ML-based algorithms, its detection accuracy improved after mitigation to a level comparable to the ML-based algorithms. These results confirm that combining false alarm mitigation with both rule-based and ML-based AFDD algorithms significantly enhances practical reliability while preserving robust fault detection capabilities. Furthermore, the findings demonstrate the potential for field deployment of these algorithms in residential HVAC systems and highlight the importance of minimizing false alarms.

False Alarm

Laser interference structuring of Cu for adhesive joining of HVAC equipment

Due to potential energy and cost savings benefits, adhesive joining has been recently considered for heating, ventilation, air conditioning, and refrigeration (HVAC&R) systems. HVAC adhesive bonding requires cost-effective and adequate surface preparations of adherents. Here, this article investigates the use of abrasion, traditional single-beam laser, and a laser-interference technique as surface preparations of copper surfaces. Surface morphology is characterized using scanning electron microscopy (SEM) and atomic force microscopy (AFM). Effective submicrometer peak-to-valley structuring with a periodicity of ∼2.7μ⁢m was demonstrated for laser-interference processing. Single-lap shear tests were conducted for 89 joints made with bondline thicknesses of 0.15 and 0.3 mm. Data on process variables and measured variables included open-time, bond length, maximum load, displacement at failure, shear lap strength, and failure mode. A statistical analysis was conducted on each lot to determine the lower limit with 95% confidence intervals for displacements at failure and shear lap strengths. A comparison is presented between the properties of laser-structured joints with respect to those prepared by abrasion, which is considered the baseline surface preparation technique. Based on this comparison, one single-beam laser technique and two laser-interference techniques were shown to exhibit vastly superior performance over the joints made with abraded specimens.

Sabau, Adrian S. [Oak Ridge National Laboratory (O

Optimizing Control for Efficient Load Shifting with Thermal Energy Storage in Existing HVAC Systems

This project developed the integration of a direct-contact heat exchanger (DCHX) based thermal energy storage (TES) system with a chiller–air handling unit (AHU) plant to evaluate its potential for reducing building energy costs. Detailed physical models of the TES unit, building envelope, and HVAC components were developed alongside simplified control-oriented models to support both high-fidelity simulation and real-time optimization. Two control strategies were implemented and compared: a rule-based control (RBC) aligned with utility time-of-use (ToU) rates, and a model predictive control (MPC) framework leveraging forecasts of building load, weather, and internal gains. Simulation results show that the RBC strategy reduced daily electricity costs by around 30% by shifting cooling production from on-peak to off-peak hours. In contrast, the MPC strategy achieved significantly greater performance, reducing daily operating costs by up to 44% and peak-hour costs by more than 60%. Both strategies maintained indoor thermal comfort within acceptable limits, with MPC further improving load distribution and reducing equipment cycling. The outcomes confirm that TES integration, particularly when coordinated with advanced predictive control, can provide substantial cost savings and on-peak demand reduction. . These findings directly support the U.S. Department of Energy’s goals for grid-interactive efficient buildings and demonstrate the potential of TES-enabled HVAC systems for scalable deployment across the commercial building.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI

Commercial Building HVAC Technology Challenge - Carrier (Final Report)

The purpose of this Cooperative Research and Development Agreement (CRADA) was to test two rooftop commercial heating, ventilation, and air conditioning (HVAC) systems supplied by Carrier Corporation to determine if they met the laboratory test requirements of the United States Department of Energy (DOE) Commercial Building HVAC Technology Challenge (hereafter noted as “the Challenge”). Results of the laboratory testing completed at Oak Ridge National Laboratory (ORNL) demonstrated that the systems met all requirements of the Challenge. Carrier Corporation has successfully completed this aspect of the Challenge. This CRADA report will briefly describe the Challenge, the test plan created to measure the success of systems provided by Challenge participants, and the results of laboratory testing of the Carrier commercial rooftop systems.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI

Lessons learned from the development and implementation of a workforce training curriculum for advanced controls for high performance HVAC systems

Over the past decade, academic research on advanced controls has slowly transitioned into new software platforms, giving rise to various companies developing and deploying these innovative products, including solutions for light commercial HVAC systems. However, the current workforce remains widely unprepared to install, maintain and operate these systems, particularly complex software-based control platforms, as most workforce training programs still focus on traditional building automation for large commercial buildings. This paper presents the development and piloting of curriculum for three key types of professionals: ● Technicians (trade-level): installing and maintaining modern high-performance HVAC systems and controls ● Programmers (undergrad-level): developing and implementing advanced controls ● Engineers and energy professionals (undergrad/grad-level): managing and evaluating system performance We share details of the material developed including training videos, open-source software, instruction manuals. We also present the results of a pilot implementation of the training materials with real students.

Casillas, Armando

ResStock Measure Documentation: HVAC Load Flexibility

This report is part of a series describing different ResStock(TM) measures. "Measures" refers to energy efficiency retrofits that can be applied to buildings during modeling. This documentation covers the "HVAC Load Flexibility" measure upgrade methodology and briefly discusses key results.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI

High Velocity AI Cache (HVAC)

HVAC is a high-performance caching system designed for large-scale AI training workloads.

Khan, Awais [Oak Ridge National Laboratory (ORNL),

Integration of thermally anisotropic building envelopes with TES and advanced controls to tailor HVAC loads

Heating, ventilation, and air conditioning (HVAC) systems are the primary energy consumers in buildings to meet heating or cooling energy demands. The building envelope can play an active role in reducing this demand and associated costs by collecting thermal energy naturally available, such as diurnal temperature swings, solar irradiance, and night sky radiation cooling, to offset heating and cooling loads.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI

A Probabilistic Approach to Load Modeling for Central HVAC Systems in Large Commercial Buildings for Retrofit Decisions Under Uncertainty

Retrofitting central HVAC systems in large commercial buildings with advanced technologies like heat recovery chillers (HRCs) offers a significant opportunity to enhance energy efficiency. However, analyzing these retrofits is challenging with traditional whole-building simulation tools, which require intensive calibration and struggle to model innovative system configurations and controls. To overcome these limitations, this study proposes a load profilebased retrofit analysis framework that provides better decisions under uncertainty. The main focus of this paper is the development of a probabilistic load profile model that can be used in the framework by using exploratory data analysis (EDA) of measured building data to properly quantify its inherent variability. A non-parametric Gaussian Process (GP) model was employed to capture the time- and weather-dependent characteristics of the heating load while explicitly modeling its uncertainty. The model's effectiveness is demonstrated through strong predictive performance on unseen data and physically interpretable insights into load behavior. This data-driven, probabilistic load profile serves as a robust and flexible input for subsequent system simulations, enabling a more confident and statistically sound analysis of retrofit potential.

Ham, S W

HVAC modifications and computerized energy analysis for the Operations Support Building at the Mars Deep Space Station at Goldstone

The key heating, ventilation, and air-conditioning (HVAC) modifications implemented at the Mars Deep Space Station's Operation Support Building at Jet Propulsion Laboratories (JPL) in order to reduce energy consumption and decrease operating costs are described. An energy analysis comparison between the computer simulated model for the building and the actual meter data was presented. The measurement performance data showed that the cumulative energy savings was about 21% for the period 1979 to 1981. The deviation from simulated data to measurement performance data was only about 3%.

Halperin, A.

Heating Ventilation Air-Conditioning (HVAC) System Analysis and Optimization for Revit with the OpenStudio Analytical Framework (CRADA Final Report)

This project proposes to integrate the NREL-developed OpenStudio (OS) and its accompanying Analytical Framework (OSAF) into Autodesk’s (ADSK’s) market leading suite of building information modeling (BIM) tools. As a result, BIM users will gain access to advanced (but user-friendly) building energy modeling (BEM), calibration, and design optimization capabilities. Following integration, the BIM software will automatically generate a consistent OS-based BEM model, allowing users to develop projects in an integrated manner, moving back and forth between architectural and engineering perspectives without redundancy or data loss, saving time and effort.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI