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At least 109 records · Page 6

U.S. Commercial Building Stock Analysis of COVID-19 Mitigation Strategies: Preprint

The COVID-19 pandemic highlights the importance of improving building indoor air quality to reduce occupants’ chances of contracting airborne illness. The ASHRAE Epidemic Task Force (ASHRAE-ETF) released several COVID-19 mitigation strategies at the onset of the pandemic. This study explores four of those recommendations for reducing transmission of COVID-19 inside buildings: (1) 100% outdoor air ventilation, (2) MERV-13 or better filters, (3) demand control ventilation removal, and (4) HVAC flushing mode. These recommendations were simulated and assessed using ComStock, a model of the U.S. commercial building stock. The study showed the 100% outdoor air ventilation recommendation had the largest impact on energy consumption, noncoincident peak demand, and thermostat violations. Removing demand control ventilation had the smallest national aggregate impact, installing MERV-13 filters led to slight increases in energy use and peak demand, and HVAC outdoor air flushing led to modest energy use and peak demand increases.

building energy modelling↗

Decarbonizing or illusion? How carbon emissions of commercial building operations change worldwide

To lead the low-carbon transition in global buildings, this study is the first to use the generalized Divisia index method (GDIM) to identify the factors driving carbon emissions and assess the decarbonization performance in commercial building operations (CBOs) of sixteen countries during 2000–2019. Results show that (1) while the global carbon emissions from CBOs have increased at a modest rate of 0.9%/yr, this trend runs counter to the declining emissions in the U.S. (-1.1%/yr) and the significant growth in China (14.4%/yr), which can be attributed to the impact of economy-related factors. (2) The U.S. and China, as the largest emitters, contributed 66.8% of the samples’ decarbonization of CBOs (919.1 million tons of carbon dioxide). (3) Most countries’ CBOs had a decarbonization efficiency level of less than 10%, except for Spain (27.8%). Spain excelled in both areas of per capita and per floor area with an average efficiency of nearly 30%. Moreover, ridge regression successfully confirms the stability of GDIM results and it should be noted GDIM has limitations in characterizing the end-use activity. Overall, this study tracks the historical decarbonization of global CBOs and offers benchmarks for different emitters to forecast the dynamic of building emissions along with economic booms.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Field Performance of Commercial Building Load Flexibility Using Model Predictive Control

Model Predictive Control (MPC) applied to buildings is starting to see some commercial adoption by companies. However, it is hard to estimate if relative energy cost savings are enough to justify the cost of MPC implementation with few reported demonstrations. In small commercial and residential buildings, a one size-fits-all solution can help reduce implementation costs, while in very large buildings or districts the potential energy cost savings magnitude can cover more tailored solutions. This estimation becomes harder for medium to large commercial buildings, where a one-size-fits-all solution cannot be adopted and potential energy cost savings might not be sufficient to cover a tailored solution. Therefore, value propositions in addition to energy efficiency alone can make MPC technology more attractive through additional energy cost savings. One such value proposition is load shifting in response to dynamic electricity prices. On this aspect, MPC is a key technology to unlock building thermal mass for energy flexibility in response to electric grid conditions. This study shows the experimental results of MPC control of an office building in Berkeley, where different dynamic electricity price profiles were used in the MPC objective function to shift the building load and to calculate hypothetical electricity costs. Results show potential 50% cost savings with respect to the existing controller with the dynamic price scenario.

Zanetti, Ettore↗

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↗

Evaluation of thermostat location for multizone commercial building performance

In multi-zone buildings, it is often found that a single shared thermostat controls more than one conditioned zones. Although these shared zones are supposed to have similar thermal needs (e.g., cooling and heating load), in reality, they are not mainly due to different orientations, sizes of windows, occupancy, space types, etc. This can cause unnecessary energy waste or thermal discomfort for the occupants. How to quantify this impact in multizone buildings remains a research gap. Therefore, this study aims to evaluate the impact of different sensor (i.e., thermostat) locations for multizone commercial buildings through a comprehensive modeling study. Here, two different scenarios for the sensor locations were selected to evaluate the impact in terms of energy and thermal comfort. The scenario (1) is that one to five sensors distributed among the five zones, but the sensor readings from selected zones will be used for no-sensor zones, which is no-mean sensor scenario. The scenario (2) is that one to five sensors distributed among the five zones, but the average temperature from the shared zones will be used for each of the shared zones, which is a mean sensor scenario. The uncertainty analysis was performed for different sensor location scenarios.(a)The major findings from an energy perspective, for scenario (1), the differences of cooling energy go as high as 17% more or 12% less, compared with the baseline. For heating energy consumption, the discrepancies go as high as 51% more or 52% less, compared with baseline. For site energy consumption, the discrepancies go as high as 3.2% more or 3.2% less, compared with baseline. For fan energy consumption, the discrepancies go as high as 3.2% more or as low as 1.0% less, compared with baseline. For scenario (2), the discrepancies of cooling energy go as high as 3% more, or 0.5% less, compared with the baseline. For heating energy consumption, the discrepancies, are go as high as 10.1% more or as low as 3.0% less, compared with baseline. For site energy consumption, the discrepancies go as high as 1.3% more or 0.3% less, compared with baseline. For fan energy consumption, the discrepancies go as high as 3.1% more or as low as 1.0% less, compared with baseline.(b) In terms of the indoor thermal comfort, for the no-mean-sensor scenarios, the discrepancies of unmet hours for cooling mode can be as high as 1,200 h, compared with the baseline. The discrepancies of unmet hours for heating mode can be as high as 740 h, compared with the baseline. For the mean-sensor scenarios, the discrepancies of unmet hours for cooling mode can be as high as 750 h, compared with the baseline. The discrepancies of unmet hours for heating mode can be as high as 50 h, compared with the baseline.

42 ENGINEERING↗

Where and When Does Solar Plus Storage Make Sense for Commercial Buildings?

As the capital cost of battery energy storage systems (BESS) declines, opportunities for commercial buildings to achieve net savings through peak demand management and energy arbitrage are emerging. National Renewable Energy Laboratory researchers modeled energy storage project economics - with and without accompanying solar photovoltaic systems - using local utility rates, ASHRAE climate zones, and solar intensity data to identify regions where these systems deliver life cycle savings now and in future cost scenarios.

battery energy storage systems↗

Development of National New Construction Weighting Factors for the Commercial Building Prototype Analyses (2003-2018)

The U.S. Department of Energy (DOE), Office of Building Technologies tasked Pacific Northwest National Laboratory to develop construction weights for various commercial building categories for the purpose of estimating weighted national energy savings from the development of ANSI/ASHRAE/IESNA Standard 90.1-2019 compared to ANSI/ASHRAE/IESNA Standard 90.1-2016. Disaggregate construction volume data was acquired from the McGraw Hill Construction Database for the years 2003-2018 and analyzed to develop detailed construction weights by climate zones, subzones and by states. These weights are provided in this report and will be subsequently used in developing a weighted national energy savings estimate for the impact of the 2019 standard. For the current update, PNNL reviewed the same data source with the latest construction data for the years 2003-2018.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

What We Learned From Analyzing 18 Million Rows of Commercial Buildings’ HVAC Fault Data

To achieve ambitious decarbonization goals it is critical that buildings operate to their full potential. Commercial HVAC systems, however, experience a wide range of operational faults, adversely affecting energy consumption, occupant comfort, and maintenance costs. Analytical tools such as fault detection & diagnostics (FDD) software identify and help diagnose these types of sensing, mechanical, or control-related faults. While significant energy savings has been documented for FDD, along with limited-scale studies on technical capabilities, there is a lack of empirical data on faults being reported by FDD tools. With FDD deployment accelerating significantly over the past decade there is an opportunity to gather and analyze data on commercial HVAC operational problems at an unprecedented scale. Such data could address many questions such as: [a] What faults are most commonly reported?; and [b] How does fault reporting vary by time of year and other possible drivers? A recent study into FDD fault reporting amassed the largest U.S. dataset of commercial HVAC air-side fault records, drawn from multi-year monitoring across over 60,000 pieces of HVAC equipment. The results of this study provide granular data on fault reporting for over 90 unique fault types. In this paper we provide an overview of the research process and highlight key findings and lessons learned. This study presents an extraordinary level of detail on FDD fault reporting characteristics across many climate zones and building types. Armed with these new insights, commercial building industry stakeholders can make better informed decisions when designing, configuring, and operating commercial HVAC systems.

Crowe, Eliot↗

Advanced co-simulation framework for assessing the interplay between occupant behaviors and demand flexibility in commercial buildings

With buildings contributing significantly to electricity usage, enabling demand flexibility becomes a challenge, especially when accounting for occupant comfort. This study introduces an innovative co-simulation framework integrating multiple models: heating, ventilation, and air conditioning (HVAC) system, building zone load, indoor airflow, supervisory control, and occupant comfort and behavior. Uniquely, this framework allows for a comprehensive and dynamic analysis of building systems and occupant interactions in demand response events. Using this framework, we conducted a case study using a typical small office building model. Specifically, we focused on three areas: (1) the impact of indoor airflow modeling on energy use, occupant comfort, and behaviors forecasting, (2) the impact of occupant behaviors on demand flexibility, and (3) occupant comfort and behaviors under demand response events. Key performance indicators such as energy use, flexibility factor, durations of occupant discomfort and occupant behaviors were analyzed. Our findings indicated variations in energy usage and occupant comfort within demand flexibility events, marked by uncertainty boundaries, with variability in demand shedding up to 57.9%. Here, we concluded that this framework is suitable for analyzing typical commercial buildings and their HVAC systems in terms of demand flexibility potential under the impact of occupant behaviors.

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↗

Datasets of Faults in Variable Air Volume Terminal Units in a Multi-Zone Commercial Building

Faults in HVAC systems can decrease system efficiency and equipment lifespan, leading to 5%–30% of energy consumption being wasted in commercial buildings. We identified two common faults in HVAC variable air volume systems: a stuck damper fault in the variable air volume terminal unit and a discharge airflow sensor fault. We conducted three sets of damper stuck tests and two sets of airflow sensor tests, each including a fault-free scenario and scenarios with varying levels of faults, over one day. The faults were implemented in Oak Ridge National Laboratory’s two-story Flexible Research Platform building to generate a high-quality, well-controlled dataset covering fault-induced and fault-free scenarios. The test building, fault test scenarios, and data validation are described here. The open-source dataset includes 1 min intervals of weather and building data on the presence and absence of building faults. This dataset can be used to analyze the effects of HVAC system faults on system operation and indoor building conditions, and to develop or evaluate a fault detection and diagnosis algorithm.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Assessing the performance of global thermostat adjustment in commercial buildings for load shifting demand response

Abstract Efficiently leveraging new sources of flexibility is critical to mitigating load balancing challenges posed by variable renewable resources. The thermal inertia of commercial buildings allows us to shift their power consumption on minute to hourly timescales to provide demand response to the grid while maintaining occupant comfort. Global thermostat adjustment (GTA) provides a readily available and scalable approach for implementing load shifting demand response using commercial heating, ventilation, and air conditioning (HVAC) systems, since it leverages the inherent sophistication of modern building automation systems. However, there is an incomplete understanding of GTA’s performance for this purpose and its impact on building systems and occupant comfort. In this paper, we explore the performance of GTA by analyzing results from nearly nine hundred experiments on eight university campus buildings in Michigan and North Carolina. Using GTA, we manipulate each building’s thermostat setpoints causing the building to shift its power consumption with respect to its baseline. We quantify the magnitude of HVAC power response, energy use of HVAC subsystems, and impact on occupant comfort. Finally, we connect our experimental results with power system operation using an optimization model that coordinates GTA actions across a large collection of grid-interactive efficient buildings (GEBs) to reduce high ramp rates on the grid and mitigate renewable energy curtailment. Overall, our work finds that the impacts on HVAC subsystems are often complex, and may result in additional energy being consumed by fans and terminal reheat. These effects must be considered when using GTA for load shifting. Additionally, we demonstrate that occupant comfort, as assessed by indoor temperature and humidity, can be maintained during GTA events. From a societal perspective, our modeling work finds that the additional renewable energy that can be integrated through the use of GTA strategies eclipses any additional energy consumed by buildings.

Keskar, Aditya (ORCID:0000000244617980)↗

Integrated Dynamic Facade Control with an Agent-based Architecture for Commercial Buildings

Dynamic façades have significant technical potential to minimize heating, cooling, and lighting energy use and peak electric demand in the perimeter zone of commercial buildings, but the performance of these systems is reliant on being able to balance complex trade-offs between solar control, daylight admission, comfort, and view over the life of the installation. As the context for controllable energy-efficiency technologies grows more complex with the increased use of intermittent renewable energy resources on the grid, it has become increasingly important to look ahead towards more advanced approaches to integrated systems control in order to achieve optimum life-cycle performance at a lower cost. This study examines the feasibility of a model predictive control system for low-cost autonomous dynamic façades. A system architecture designed around lightweight, simple agents is proposed. The architecture accommodates whole building and grid level demands through its modular, hierarchical approach. Automatically-generated models for computing window heat gains, daylight illuminance, and discomfort glare are described. The open source Modelica and JModelica software tools were used to determine the optimum state of control given inputs of window heat gains and lighting loads for a 24-hour optimization horizon. Penalty functions for glare and view/ daylight quality were implemented as constraints. The control system was tested on a low-power controller (1.4 GHz single core with 2 GB of RAM) to evaluate feasibility. The target platform is a low-cost ($35/unit) embedded controller with 1.2 GHz dual-core cpu and 1 GB of RAM. Configuration and commissioning of the curtainwall unit was designed to be largely plug and play with minimal inputs required by the manufacturer through a web-based user interface. An example application was used to demonstrate optimal control of a three-zone electrochromic window for a south-facing zone. The overall approach was deemed to be promising. Further engineering is required to enable scalable, turnkey solutions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

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↗

Adopting occupancy-based HVAC controls in commercial building energy codes: Analysis of cost-effectiveness and decarbonization potential

Recent research has shown the energy-saving potential of occupancy-based HVAC controls (OBCs) in commercial buildings. However, building energy codes have not fully adopted this technology. This study aims to evaluate the cost-effectiveness and decarbonization benefits of OBCs and provide guidance for integrating occupancy sensors into building energy code development. To this end, a parametric simulation using EnergyPlus and a nationwide cost-effectiveness analysis are carried out considering three building types and 40 representative cities in the U.S. Here, the findings reveal that the current cost-effectiveness performance of OBCs is limited due to the high cost of occupancy sensors. However, incorporating the societal cost of carbon factor in future energy and environmental policy could greatly enhance the actual cost-effectiveness performance. Besides, a reduction in the cost of occupancy sensors to approximately 60% of the current price level could also greatly shorten the discounted payback period of OBCs. Additionally, OBCs demonstrate significant potential in building decarbonization, with potential CO 2 emissions savings of more than 5.56 million metric tons across the three building types and 40 selected cities. Finally, policy implications are provided to guide the incorporation of occupancy-based HVAC controls in future energy codes.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

The application of photovoltaic roof shingles to residential and commercial buildings

The recent development of a shingle-type solar-cell module makes it possible to incorporate easily photovoltaic power generation into the sloping roofs of residential or commercial buildings. These modules, which use a closely packed array of nineteen 53-mm-diameter circular solar cells, are capable of producing 101 watts/sq m of module area under standard operating conditions. This module performance is achievable by the use of solar cells with an average efficiency of 13.3 percent at 1 kW/sq m air-mass-1.5 insolation and at a cell temperature of 28 C. When these modules are mounted on a sloping south-facing roof which is insulated on the rear surface, the annual energy generated at the maximum power operating point will vary from 255.6 to 137.3 kWh/sq m of module area depending on the site location, with Albuquerque, NM, and Seattle, WA, representing the highest and lowest values of the thirteen sites considered.

Shepard, N. F., Jr.↗

Solar-Energy System for a Commercial Building--Topeka, Kansas

Report describes a solar-energy system for space heating, cooling and domestic hot water at a 5,600 square-foot (520-square-meter) Topeka, Kansas, commercial building. System is expected to provide 74% of annual cooling load, 47% of heating load, and 95% of domestic hot-water load. System was included in building design to maximize energy conservation.

Source record↗

A Critical Exploration of the Efficiency Impacts of Demand Response From HVAC in Commercial Buildings

Increasing quantities of renewable energy generation has yielded a need for greater energy storage capacity in power systems. Thermal storage in variable air volume (VAV) heating, ventilation, and air conditioning (HVAC) in commercial buildings has been identified as an inexpensive source of grid storage, but the true costs are not known. Recent literature explores the inefficiency associated with providing grid services from these HVAC-based demand response (DR) resources by employing a battery analogy to calculate round-trip efficiency (RTE). Results vary significantly across studies and in some cases reported efficiencies are strikingly low. This article has three objectives to address these prior results. First, we synthesize and expand on insights into existing literature by systematically exploring the potential causes for the discrepancies in results. We reinforce previous work indicating baseline modeling may drive differences across studies and deduce that control accuracy plays a role in the major differences between experiments and simulation. Second, we discuss why the RTE metric is problematic for DR applications, discuss another proposed metric, additional energy consumption (AEC), and propose an extension, which we call uninstructed energy consumption (UEC), to evaluate DR performance. Finally, we explore the merits of different metrics using experimental data and highlight UEC's reduced sensitivity to the characteristics of the DR signal than previously proposed metrics.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗