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At least 757 records · Page 42

Modeling the effect of climate change on U.S. state-level buildings energy demands in an integrated assessment framework

As long-term socioeconomic transformation and energy service expansion show large spatial heterogeneity, advanced understanding of climate impact on building energy use at the sub-national level will offer useful insights into climate policy and regional energy system planning. In this study, we presented a detailed building energy model with a U.S. state-level representation, nested in the GCAM integrated assessment framework. We projected state-level building energy demand and its spatial pattern over the century, considering the impact of climate change based on the estimates of heating and cooling degree days derived from downscaled USGS CASCaDE temperature data. The result indicates that climate change has a large impact on heating and cooling building energy and fuel use at the state level, exhibiting large spatial heterogeneity across states (ranges from -10% to +10%). The sensitivity analysis reveals that the building energy demand is subject to multiple key factors, such as the magnitude of climate change, the choice of climate models, and the growth of population and GDP, and that their relative contributions vary greatly across the space. The scale impact in building energy use modeling highlights the importance of constructing a building energy model with the spatially-explicit representation of socioeconomics, energy system development, and climate change. These findings will help the climate-based policy decision and energy system, especially utility planning related to building sector at the U.S. state and regional level facing the potential climate change.

Building Energy Demand, Climate Change Impact, Sta↗

Ten questions on building stock modeling to inform energy efficiency and sustainability

To enhance economic competitiveness and ensure energy efficiency, resilience, and security, cities and governments are adopting technologies and strategies to improve their existing building stocks. This approach aims to reduce energy use, improve energy affordability, and ensure a reliable power supply while safeguarding occupants during extreme weather events that may disrupt energy services. The effectiveness of these solutions will depend on building stock characteristics, use patterns, weather conditions, evolving technologies and their markets, and a city’s socio-economic conditions. This paper presents ten questions and answers that highlight the most important issues regarding the use of building stock modeling as a powerful tool to provide insights for informing stakeholders’ actions and decision-making on energy efficiency, costs reduction, and resilience of buildings in cities. Building stock modeling should build upon the fit-for-purpose framework, balancing the use case accuracy requirements, level of complexity, and needed resources (expertise, compute). The advancements in Artificial Intelligence (AI), the increasingly available open dataset of building stock in cities, and the more affordable powerful computing will accelerate the adoption of building stock modeling across scales by researchers and practitioners to inform decision making on sustainability and efficiency.

AI↗

Assessing the hygrothermal performance of bio-based materials in building wall systems

Building envelope systems are crucial in regulating thermal and moisture exchange between interior and exterior environments, accounting for approximately 28 % of building energy consumption in the United States with walls being the primary contributors. Improper selection of building envelope materials can lead to moisture-related issues, reduced resilience, and compromised durability. Hygrothermal performance assessment is a key factor in efficient building design. As such, improving the energy and hygrothermal performance of opaque wall materials, through careful assessment of material choices, is essential to enhancing building resilience, lowering energy costs, and improving occupant comfort. As the building industry seeks new strategies to reduce material energy intensity, bio-based materials emerge as a promising solution. However, their long-term hygrothermal performance in building envelope systems remains underexplored. To fill this gap, this study evaluates the hygrothermal behavior of 13 bio-based materials in residential wall systems across three U.S. climate zones. Laboratory experiments were performed to measure material properties such as density, thermal conductivity, moisture transmission, and sorption isotherms. These data were integrated into the WUFI® simulation tool to assess wall hygrothermal performance in Houston, Baltimore, and Chicago. A three-phase modeling approach was used: (1) baseline residential walls with oriented strand board (OSB) and gypsum board; (2) replacing OSB with bio-based materials; and (3) replacing drywall with bio-based materials. Results showed that the evaluated bio-based materials maintained acceptable moisture thresholds of ≤ 16 % across all climates, confirming their viability as an alternative for current sheathing materials. Furthermore, this study provides a foundation for future research and innovation in material science on the use of certain bio-based materials in high-performance, low energy use residential construction. Ultimately, providing critical data, offering a database of bio-based material properties, and supplying a simulation-based approach will help designers make informed decisions for future efficient building practices.

Bio-based materials↗

A multi-scale calibration approach for process-oriented aggregated building energy demand models

Long-term energy planning relies largely on projections of future energy demand and hourly load profiles. Aggregate building models are increasingly being utilized to characterize the sensitivity of current and future building stocks to changes in climate, population, and building technology on city-to-regional-to-national scales. Due to challenges in the availability of data, those analyses have been limited to projection of energy demand at a single scale, usually state or country, while long-term planning power system models and production cost models might operate at different spatial scales such as energy regions which are focused on ensuring adequate generation infrastructure. In this work, we propose and evaluate a novel method to calibrate an aggregate building energy demand model (PNNL’s BEND model) against the best available data at the spatial scale of balancing authorities. This approach extends previous work on aggregated building energy demand by facilitating analysis of building energy demand across scales, in particular policy and operational decision-making scales. We show that the bias-corrected model estimates building electric loads reasonably well compared with estimates from a statistical model, but has the additional feature of flexibility across spatial scales. While the calibration approach is presently U.S.-centric and associated with U.S. energy regions, it can be extrapolated to other worldwide regions with similar scale challenges between policy and operational implementation decision making. We discuss the significant challenges involved in formulating and calibrating a complex physical model based on simulations of roughly 100,000 individual buildings against available aggregate regional electric load data and highlight areas for potential future work and improved data collection.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Device-level plug load disaggregation in a zero energy office building and opportunities for energy savings

Along with heating, cooling, ventilation, and lighting, plug loads are one of the principal consumers of energy in commercial buildings. Managing ever-changing plug loads is a great challenge given the quantity and variety of devices in commercial buildings and the cost of monitoring equipment. To address this issue, we propose a method for developing a disaggregated model of an office building's plug loads that utilizes power data from a small portion of monitored devices and a device inventory. Using data from metering and control devices in the Research Support Facility at the National Renewable Energy Laboratory, we compared our model to the building's plug load submeters. We found that the model was effective in predicting the shape of the building's average plug loads; however, it did not account for the entire magnitude of the load. With the disaggregated breakdown, we identified devices that contributed significantly to the building's unoccupied load, such as the audio visual equipment as well as devices that contributed significantly at specific times of the day, such as the microwaves at noon. This disaggregated information enables building owners to make more informed decisions with respect to plug load controls and energy efficiency upgrades. Furthermore, we highlight how the plug loads in the Research Support Facility have changed over time and offer recommendations for implementing this disaggregation method in other buildings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

The good, the bad, and the ugly: Data-driven load profile discord identification in a large building portfolio

Reducing the overall energy consumption and associated greenhouse gas emissions in the building sector is essential for meeting our future sustainability goals. Recently, smart energy metering facilities have been deployed to enable monitoring of energy consumption data with hourly or subhourly temporal resolution. This unprecedented data collection has created various opportunities for advanced data analytics involving load profiles (e.g., building energy benchmarking programs, building-to-grid integration, and calibration of urban-scale energy models). These applications often need preprocessing steps to detect daily load profile discords, such as: 1) outliers due to system malfunctions (the bad) and 2) irregular energy consumption patterns, such as those resulting from holidays (the ugly) compared to normal consumption patterns (the good). However, current preprocessing methods predominantly focus on filtering using statistical threshold values, which fail to capture the contextual discords of daily profiles. In addition, discord detection algorithms in building research are often aimed at finding individual building-level discords, which are not suitable at a large scale. Thus, here, we develop a method for automated load profile discord identification (ALDI) in a large portfolio of buildings (more than 100 buildings). Specifically, ALDI 1) uses the matrix profile (MP) method to quantify the similarities of daily subsequences in time series meter data, 2) compares daily MP values with typical-day MP distributions using the Kolmogorov-Smirnov test, and 3) identifies daily load profile discords in a large building portfolio. We evaluate ALDI using the metering data of both an academic campus and a residential neighborhood. Our results demonstrate that ALDI efficiently discovers measurement errors by system malfunctions and low energy consumption days in the academic campus portfolio, and it detects unique load shape patterns likely driven by occupant behavior and extreme weather conditions in the residential neighborhood.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Experimental investigation on thermal inertia characterization of commercial buildings for demand response

Characterizing the thermal inertia of commercial buildings is of great importance in quantifying demand flexibility. Experimental tests can be used to investigate the thermal inertia of commercial buildings. However, existing studies tend to be qualitative and have limited scope. In this study, a comprehensive field test has been performed to assess the thermal inertia of commercial buildings. In this field test, six buildings are selected with different sizes, vintages, and types of heating, ventilation, and air conditioning (HVAC) systems to represent the majority of the U.S. commercial building stock. We quantify the thermal inertia with building operation data collected under various thermostat excitation signals. We then studied the relationship between thermal inertia and intrinsic properties, such as floor area, HVAC system, etc., as well as the operation condition indicators such as outdoor air temperature, zone temperature, and occupancy. The testing results indicate that the median values of the normalized charge response time and the normalized discharge response time of the five buildings are 1~5 hr/ °C and -5~-1 hr/ °C, respectively. The results also show that the thermal inertia of commercial buildings may be sensitive to the HVAC system type but not the floor area or location of zones, i.e., core vs. perimeter. Finally, our results suggest that the relationships between the charging/discharging normalized response time and the zone/outdoor temperature may vary among zones and be highly nonlinear.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

The metal alloys from the XIX century and weathering action in the Mercado do Ver-o-Peso building, northern Brazil: Identification with the usage of laboratory analysis

The fabrication of metallic buildings started in Europe after the Industrial Revolution in the 18th century. Metallic constructions became very popular, and started being imported by several countries, due to the facility of constructing or assembling. Belém, a northern Brazilian city, holds a great number of buildings entirely made of iron, including the Ver-o-Peso, a fish market which structures were imported from England by the end of the 19th century. This building represents a unique type of architecture and it's an important part of the city's heritage. However, research so far did not focus on its construction materials. Ver-o-Peso building's metal alloys haven't been thoroughly studied concerning physical, chemical and mineralogical characterizations. This paper aims to identify the types of metal alloys used in the building, and also corrosion products' result from weathering actions. The methods used to characterize the materials were scanning electron microscopy and X-ray diffraction. Through this research it was possible to identify four types of iron alloys used in the different parts of the building, characterize the paint coats, and determine types of corrosion. The characterization of the materials in the building allows enrolling basis for restoration processes, documenting the types of metal alloy used in architectural heritage from the 19th century, as well as understanding the advances of corrosion. - Highlights: • Ver-o-peso is a heritage building from the 19th century with unidentified alloys. • Alloy and weathering product characterization was done using SEM/EDS and XRD. • Four metal alloy types were described, indicating different types of foundries. • Weathering products showed distinct mineral phases and physical characteristics. • Original paint coats were found among corrosion products.

36 MATERIALS SCIENCE↗

Creating high performance buildings: Lower energy, better comfort

Buildings play a critical role in the challenge of mitigating and adapting to climate change. It is estimated that buildings contribute 39% of the total U.S. greenhouse gas (GHG) emissions [1] primarily due to their operational energy use, and about 80% of this building energy use is for heating, cooling, ventilating, and lighting. An important premise of this paper is about the connection between energy and comfort. They are inseparable when one talks about high performance buildings. Worldwide data suggests that we are significantly overcooling buildings in the summer, resulting in increased energy use and problems with thermal comfort. In contrast, in naturally ventilated buildings without mechanical cooling, people are comfortable in much warmer temperatures due to shifting expectations and preferences as a result of occupants having a greater degree of personal control over their thermal environment; they have also become more accustomed to variable conditions that closely reflect the natural rhythms of outdoor climate patterns. This has resulted in an adaptive comfort zone that offers significant potential for encouraging naturally ventilated buildings to improve both energy use and comfort. Research on other forms for providing individualized control through low-energy personal comfort systems (desktop fans, foot warmed, and heated and cooled chairs) have also demonstrated enormous potential for improving both energy and comfort performance. Studies have demonstrated high levels of comfort with these systems while ambient temperatures ranged from 64–84°F. Energy and indoor environmental quality are inextricably linked, and must both be important goals of a high performance building.

42 ENGINEERING↗

Occupancy schedule development and its effect on OpenStudio prototype college building model

College buildings have unique characteristics compared with school buildings. Therefore, defining the realistic occupancy schedule in a prototype college building has significant research opportunities. In this study, the actual operating schedules of each space type were collected and generated based on the class reservation schedule and compared with the previous reference schedule (primary/secondary school). Here, the schedules were analyzed for their effect on the OpenStudio prototype college building model. The findings highlight that the use of a typical school building schedule in a college building impairs the granularity of information. The analysis shows significant differences between the previous occupancy schedule and the updated occupancy schedule of the college building, leading to a considerable decrease in occupancy density. Furthermore, the effect of these occupancy pattern changes on the prototype building model is examined. The variations were observed in minimum ventilation requirements, the average mechanical ventilation rate, and energy consumption attributed to changes in occupancy density.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Optimal Energy Dispatch Controller for Fuel Cell-Integrated Multi-Zone Building

Stationary fuel cells provide potential opportunities for energy savings when integrated with buildings. Through smart dispatch of both electrical power and heat generated by the fuel cells and managing the building loads, the buildings can achieve more efficient operation. In this paper, we develop an optimal energy dispatch controller to operate a fuel cell-integrated building. The controller leverages the inherent thermal storage and the dispatchable fuel cell to reduce its operating cost and to allow the building to participate in grid services. The proposed controller is implemented on two types of commercial buildings, a large office building and a large hotel, and the effectiveness of the controller is demonstrated through simulations. The results also indicate that the potential saving varies significantly with different system parameters, including season, fuel prices, and equipment sizing, which provide helpful insights for building operators and other stake holders.

39 EE - Hydrogen and Fuel Cell Technologies (EE-3F↗

Performance-based earthquake early warning for tall buildings

The ShakeAlert Earthquake Early Warning (EEW) system aims to issue an advance warning to residents on the West Coast of the United States seconds before the ground shaking arrives, if the expected ground shaking exceeds a certain threshold. However, residents in tall buildings may experience much greater motion due to the dynamic response of the buildings. Therefore, there is an ongoing effort to extend ShakeAlert to include the contribution of building response to provide a more accurate estimation of the expected shaking intensity for tall buildings. Currently, the supposedly ideal solution of analyzing detailed finite element models of buildings under predicted ground-motion time histories is not theoretically or practically feasible. The authors have recently investigated existing simple methods to estimate peak floor acceleration (PFA) and determined these simple formulas are not practically suitable. Instead, this article explores another approach by extending the Pacific Earthquake Engineering Research Center (PEER) performance-based earthquake engineering (PBEE) to EEW, considering that every component involved in building response prediction is uncertain in the EEW scenario. Additionally, while this idea is not new and has been proposed by other researchers, it has two shortcomings: (1) the simple beam model used for response prediction is prone to modeling uncertainty, which has not been quantified, and (2) the ground motions used for probabilistic demand models are not suitable for EEW applications. In this article, we address these two issues by incorporating modeling errors into the parameters of the beam model and using a new set of ground motions, respectively. We demonstrate how this approach could practically work using data from a 52-story building in downtown Los Angeles. Using the criteria and thresholds employed by previous researchers, we show that if peak ground acceleration (PGA) is accurately estimated, this approach can predict the expected level of human comfort in tall buildings.

58 GEOSCIENCES↗

GT Flex: A Coordinated Multi-Building Pilot Study

Buildings are a significant and untapped resource for providing utility electric grid services. Recent studies have estimated that buildings could reduce the peak demand on the electric grid in the U.S. by almost 25% through effective combinations of energy efficiency (EE) measures and load flexibility strategies (Langevin et al. 2021). The U.S. Department of Energy (DOE) has established a goal to triple energy efficiency and demand flexibility in both residential and commercial sections by 2030 compared to 2020 levels (Satchwell et al. 2021). Such findings place buildings alongside electric vehicles, photovoltaics, electric batteries, and other distributed energy resources (DERs) as primary technologies needed for supporting high renewable energy generation grids. Coordinating and optimizing multiple buildings and other DERs is more beneficial and valuable when compared with individual buildings and DERs operating as siloed resources, uncoordinated with others (Olgyay et al. 2020). A pilot study at the Georgia Institute of Technology (GIT) was conducted to evaluate value propositions of a multi-building scale project seeking carbon reduction, energy efficiency and grid-interactive capabilities, by demonstrating the means by which stakeholders can determine the technical and financial merits of grid-interactivity and energy efficiency technologies coordinated across multiple assets. The study focused on analyzing technical feasibility of deploying thermal load flexibility strategies at the multi-building scale, coordinated to not exceed existing infrastructure constraints at the pilot site. Results show that campus can provide 3-3.5 MW of potential load shed over a 4-hour event window through coordinated dispatch of thermal cooling load flexibility without exceeding existing infrastructure capacities. Under future high renewable scenarios, this thermal flexibility resource is also valuable when coordinated to reduce curtailment of intermittent renewables. Economic analyses were performed to effectively communicate various value propositions of grid-interactive and efficient building (GEB) thermal flexibility strategies. Load flexibility presents a financial value proposition to the campus today. By conducting rationalized, coordinated dispatch in response to real time price (RTP) fluctuations, the campus can benefit materially from daily price arbitrage. The RTP signal acts as an aggregating mechanism between the utility and customer to call on demand flexibility resources, with a large portion of the benefit deriving from a relatively small number of days. Realizing and maximizing this benefit with thermal load flexibility requires careful attention to the timing of pricing signals and parameterization of dispatch to overcome efficiency penalties. Grid value and signals are expected to evolve over time, and thermal load flexibility shows potential to adapt dispatch logic to support intermittent renewable generation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Report Series: Evaluation, Finding Of Effect, And Mitigation Documentation For Building 23-113, Mercury, Area 23, Nevada National Security Site, Nye County, Nevada

The U.S. Department of Energy (DOE) National Nuclear Security Administration Nevada Field Office (NNSA/NFO) plans to demolish Building 23-113 in Mercury (Nevada State Historic Preservation Office [SHPO] Resource No. B15236), which is on the Nevada National Security Site (NNSS) in Nye County, Nevada. Demolition of Building 23-113 is part of the long-term project to modernize the town of Mercury on the NNSS for future mission needs. The project is considered an undertaking subject to review under Title 54 of United States Code (USC) § 306108, commonly known as Section 106 of the National Historic Preservation Act, Title 54 USC § 300101, et seq., and its implementing regulations, Title 36 of the Code of Federal Regulations (36 CFR) Part 800. In 2018, Desert Research Institute (DRI) completed an architectural survey of the town of Mercury. This effort resulted in the identification, recordation, and evaluation of the Mercury Historic District (MHD, SHPO Resource No. D230), including the identification of its contributing elements (Reno et al. 2018). The MHD was recommended eligible for listing in the National Register of Historic Places (NRHP, National Register) under the Secretary of the Interior’s (SOI) Significance Criteria A and C, as defined in 36 CFR Part 60.4, as a significant concentration of buildings and structures with a direct and important association with Cold War-era nuclear testing from 1951 through 1992. It has not been evaluated under Criteria B and D to date. As part of a larger modernization program for Mercury, the NNSA/NFO and the SHPO executed the 2018 Programmatic Agreement between the National Nuclear Security Administration Nevada Field Office and the Nevada State Historic Preservation Officer regarding Modernization and Operational Maintenance of the Nevada National Security Site, at Mercury in Nye County, Nevada (the Mercury PA). The Mercury PA includes streamlined Section 106 procedures for undertakings in the MHD based on contributing element categories. Building 23-113 is identified in Appendix C of the Mercury PA as a Category I contributing element, indicating that it might be individually eligible for the NRHP. It is a historic property for the purposes of Section 106 compliance and subject to the stipulations of the Mercury PA. Per Stipulation VI of the Mercury PA, when the Area of Potential Effect (APE) for an undertaking includes Category I elements, the NNSA/NFO must evaluate the Category I elements for individual NRHP eligibility under all of the SOI Significance Criteria prior to initiating any activity that may affect the elements. Therefore, the purpose of this report is to evaluate Building 23-113 as a potential individually eligible historic property in fulfillment of Stipulation VI of the Mercury PA. The evaluation detailed herein concludes that although Building 23-113 is significant at the local level for its important role as a recreational facility on the NNSS, the building lacks sufficient integrity to convey its significance. It is not individually eligible for listing in the NRHP at any level. The building remains eligible as a contributing element to the MHD.

54 ENVIRONMENTAL SCIENCES↗

Alaska's Rural Building Stock: a Validation Study Using ResStock and Field Data

The availability of accurate national data on demographics, building stock, and energy use is vital for modeling residential buildings and evaluating decarbonization strategies. However, rural and Indigenous populations, including those in rural Alaska, are typically underrepresented in these datasets. These communities face unique challenges due to their remote locations, severe weather conditions, and limited access to resources, resulting in high energy burden. This report examines how rural Alaskan communities are underrepresented in the ResStock housing model and highlights the need for improved data to address their unique housing and energy challenges. Thus, this report examines the representation of rural Alaskan communities within the national housing stock model, ResStock. A validation study was conducted, considering ResStock, Field Data and Aerial and 3D-view data collection (A3DDC) datasets. The validation process started by using the down selecting approach on the ResStock building stock dataset. For the purpose of this study, only the rural Alaska Boroughs and Census areas located in ASHRAE IECC Climate Zone 8 were considered to ensure a more accurate and fair comparison with the field data, which was collected in rural areas located in climate zone 8, specifically within the Nome Census area. While ResStock may accurately represent several characteristics of the building stock for rural Alaska, some differences between modeled, field data, and aerial and 3D-view data collection datasets were identified. The following building characteristics have a high impact on modeled energy consumption and demonstrated large differences: Revisit heating setpoints and consider a substantially higher setpoint distribution, it could potentially address "missing loads" if this is the case. Develop and include Toyo heating in future modeling for ResStock and EnergyPlus. Remove natural gas as a water heater fuel type outside of North Slope County. Foundation type updated to have more crawlspaces rather than basements. Infiltration rates need reexamination for a larger distribution toward higher infiltration rates. Include more vinyl and less brick in exterior wall type and revise wall color for greater proportion of light rather than dark color. Roof material revised from majority shingles to majority metal. Update number of occupants to higher number of occupant count. Building orientation represents a higher proportion of south facing buildings rather than relatively equal. The findings suggest that updating ResStock's probability logic could better represent rural Alaskan buildings. ResStock can be utilized to identify the best upgrades or energy efficiency and energy efficiency improvements, helping community leaders in making more informed decisions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

A Perspective of Decarbonization Pathways in Future Buildings in the United States

The commitment of electrification and decarbonization goals in the United States (U.S.) will significantly change the performance of future buildings. To meet these goals, it is critical to summarize the existing research related to building electrification and decarbonization and discuss future research pathways. This paper provides a perspective on decarbonization pathways of future buildings in the U.S. A critical review of the existing research was conducted, which is divided into three closely linked categories: technologies, economic impacts, and code regulations. Technologies support investments and code regulations while marketing affects the design of building codes and standards. In the meantime, code regulations guide the development of technologies and marketing. Based on the review, future potential research directions for building decarbonization are then discussed. Due to the needs of building decarbonization, future research will be multidisciplinary, conducted at a large geographic scale, and involve a multitude of metrics, which will undoubtedly introduce new challenges. The perspective presented in this paper will provide policy-makers, researchers, building owners, and other stakeholders with a way to understand the impact of electrification and decarbonization of future buildings in the U.S.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Interactive Buildings: A Review

Buildings are widely regarded as potential sources for demand flexibility. The flexibility of thermal and electric load in buildings is a result of their interactive nature and its impact on the building’s performance. In this paper, the interaction of a building with the three interaction counterparts of the physical environment, civil infrastructure networks and other buildings is investigated. The literature review presents a wide variety of pathways of interaction and their associated potential impacts on building performance metrics such as net energy use, emissions, occupant comfort and operational cost. It is demonstrated that all of these counterparts of interaction should be considered to harness the flexibility potential of the buildings while maintaining other buildings performance metrics at a desired level. Juxtaposed with the upside potential for providing demand flexibility, numerous implementation challenges are identified that are associated with the evaluation and financial valuation of the capacity for demand flexibility, the aggregated flexibility potential, as well as the control and communication to facilitate the interactions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

A technical framework to describe occupant behavior for building energy simulations

Green buildings that fail to meet expected design performance criteria indicate that technology alone does not guarantee high performance. Human influences are quite often simplified and ignored in the design, construction, and operation of buildings. Energy-conscious human behavior has been demonstrated to be a significant positive factor for improving the indoor environment while reducing the energy use of buildings. In our study we developed a new technical framework to describe energy-related human behavior in buildings. The energy-related behavior includes accounting for individuals and groups of occupants and their interactions with building energy services systems, appliances and facilities. The technical framework consists of four key components: i. the drivers behind energy-related occupant behavior, which are biological, societal, environmental, physical, and economical in nature ii. the needs of the occupants are based on satisfying criteria that are either physical (e.g. thermal, visual and acoustic comfort) or non-physical (e.g. entertainment, privacy, and social reward) iii. the actions that building occupants perform when their needs are not fulfilled iv. the systems with which an occupant can interact to satisfy their needs The technical framework aims to provide a standardized description of a complete set of human energy-related behaviors in the form of an XML schema. For each type of behavior (e.g., occupants opening/closing windows, switching on/off lights etc.) we identify a set of common behaviors based on a literature review, survey data, and our own field study and analysis. Stochastic models are adopted or developed for each type of behavior to enable the evaluation of the impact of human behavior on energy use in buildings, during either the design or operation phase. We will also demonstrate the use of the technical framework in assessing the impact of occupancy behavior on energy saving technologies. The technical framework presented is part of our human behavior research, a 5-year program under the U.S. - China Clean Energy Research Center for Building Energy Efficiency.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗