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At least 667 records · Page 37

End-Use Savings Shapes Measure Documentation: Console Water-to-Air Geothermal Heat Pump

Executive Summary Building on the successfully completed effort to calibrate and validate the U.S. Department of Energy’s ResStock™ and ComStock™ models over the past several years, the objective of this work is to produce national datasets that empower analysts working for federal, state, utility, city, and manufacturer stakeholders to answer a broad range of analysis questions. The goal of this work is to develop energy efficiency, electrification, and demand flexibility end-use load shapes (electricity, gas, propane, or fuel oil) that cover most of the high-impact, market-ready (or nearly market-ready) measures. An end-use savings shape is the difference in energy consumption between a baseline building and a building with an energy efficiency, electrification, or demand flexibility measure applied. It results in a time series profile that is broken down by end use and fuel (electricity or on-site gas, propane, or fuel oil use) at each time step. ComStock is a highly granular, bottom-up model that uses multiple data sources, statistical sampling methods, and advanced building energy simulations to estimate the annual sub-hourly energy consumption of the commercial building stock across the United States. The baseline model intends to represent the U.S. commercial building stock as it existed in 2018. This measure models the conversion of an existing heating, ventilating, and air-conditioning (HVAC) system to a series of “console” water-to-air heat pumps served by a ground heat exchanger. Console water-to-air geothermal heat pumps (GHP) are all-in-one packages that have no or minimal ductwork and serve individual spaces. Properly designed ground heat exchanger-coupled systems can offer benefits in energy efficiency relative to “conventional” HVAC systems, as well as facilitating beneficial electrification. Console GHPs can be coupled to a ground loop on the source side and can directly replace electric baseboard heaters or air-source packaged terminal heat pumps. Console GHPs can also bring in outdoor air for ventilation. This measure will be referred to throughout the document as the “Console GHP” upgrade.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

A concept of integrated environmental approach for building upgrades and new construction: Part 1—setting the stage

This article highlights the need for an active role for building physics in the development of near-zero energy buildings while analyzing an example of an integrated system for the upgrade of existing buildings. The science called either Building Physics in Europe or Building Science in North America has so far a passive role in explaining observed failures in construction practice. In its new role, it would be integrating modeling and testing to provide predictive capability, so much needed in the development of near-zero energy buildings. The authors attempt to create a compact package, applicable to different climates with small modifications of some hygrothermal properties of materials. This universal solution is based on a systems approach that is routine for building physics but in contrast to separately conceived sub-systems that are typical for the design of buildings today. One knows that the building structure, energy efficiency, indoor environmental quality, and moisture management all need to be considered to ensure durability of materials and control cost of near-zero energy buildings. These factors must be addressed through contributions of the whole design team. The same approach must be used for the retrofit of buildings. As this integrated design paradigm resulted from demands of sustainable built environment approach, building physics must drop its passive role and improve two critical domains of analysis: (i) linked, real-time hygrothermal and energy models capable of predicting the performance of existing buildings after renovation and (ii) basic methods of indoor environment and moisture management when the exterior of the building cannot be modified.

Building physics↗

City and County Commercial Building Inventories

The Commercial Building Inventories provide modeled data on commercial building type, vintage, and area for each U.S. city and county. Please note this data is modeled and more precise data may be available through county assessors or other sources. Commercial building stock data is estimated using CoStar Realty Information, Inc. building stock data. This data is part of a suite of state and local energy profile data available at the "State and Local Energy Profile Data Suite" link below and builds on Cities-LEAP energy modeling, available at the "EERE Cities-LEAP Page" link below. Examples of how to use the data to inform energy planning can be found at the "Example Uses" link below.

Array↗

Using the BEopt Automated Residential Simulation Test Suite to Enable Comparative Analysis Between Energy Simulation Engines: Preprint

Verification and validation are crucial software quality control procedures when developing and implementing models. This is particularly important as a variety of stakeholders rely on accurate predictions from building simulation programs. This study uses the BEopt Automated Residential Simulation Test Suite (BARTS) to facilitate comparison of two energy simulation engines across various building components and includes models that isolate the impacts of specific building components on annual energy consumption. As a case study, BARTS has been used to identify important discrepancies between the engines for several components of the building models; these discrepancies are caused by differences in the models used by the engines or coding errors.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Transfer learning for smart buildings: A critical review of algorithms, applications, and future perspectives

Smart buildings play a crucial role toward decarbonizing society, as globally buildings emit about one-third of greenhouse gases. In the last few years, machine learning has achieved a notable momentum that, if properly harnessed, may unleash its potential for advanced analytics and control of smart buildings, enabling the technique to scale up for supporting the decarbonization of the building sector. In this perspective, transfer learning aims to improve the performance of a target learner exploiting knowledge in related environments. The present work provides a comprehensive overview of transfer learning applications in smart buildings, classifying and analyzing 77 papers according to their applications, algorithms, and adopted metrics. The study identified four main application areas of transfer learning: (1) building load prediction, (2) occupancy detection and activity recognition, (3) building dynamics modeling, and (4) energy systems control. Furthermore, the review highlighted the role of deep learning in transfer learning applications that has been used in more than half of the analyzed studies. The paper also discusses how to integrate transfer learning in a smart building's ecosystem, identifying, for each application area, the research gaps and guidelines for future research directions.

Pinto, G↗

IEA EBC Annex 66: Definition and simulation of occupant behavior in buildings

Here, more than 30% of the total primary energy in the world is consumed in buildings. It is crucial to reduce building energy consumption in order to preserve energy resources and mitigate global climate change. Building performance simulations have been widely used for the estimation and optimization of building performance, providing reference values for the assessment of building energy consumption and the effects of energy-saving technologies. Among the various factors influencing building energy consumption, occupant behavior has drawn increasing attention. Occupant behavior includes occupant presence, movement, and interaction with building energy devices and systems. However, there are gaps in occupant behavior modeling as different energy modelers have employed varied data and tools to simulate occupant behavior, therefore producing different and incomparable results. Aiming to address these gaps, the International Energy Agency (IEA) Energy in Buildings and Community (EBC) Programme Annex 66 has established a scientific methodological framework for occupant behavior research, including data collection, behavior model representation, modeling and evaluation approaches, and the integration of behavior modeling tools with building performance simulation programs. Annex 66 also includes case studies and application guidelines to assist in building design, operation, and policymaking, using interdisciplinary approaches to reduce energy use in buildings and improve occupant comfort and productivity. This paper highlights the key research issues, methods, and outcomes pertaining to Annex 66, and offers perspectives on future research needs to integrate occupant behavior with the building life cycle.

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Application of the DNAS framework expansion to occupant population synthesis

Research in occupant behaviour is now using a more elaborate framework of building occupant interaction. Researchers often face challenges in collecting data, particularly for the data to meet the minimum number of required data points and the data interoperability requirements. Researchers address the first issue with the synthetic population and the latter with data ontologies. While synthetic population is commonly used to address the first issue, data ontology development is used to address the latter. The two solutions are complementary to each other. One of the known ontologies in building occupant behaviour research is the Drivers-Needs-Actions-Systems (DNAS) ontology, which has been used by building modelers to describe energy-related occupant behaviour. This paper describes the ontology-based synthetic population generation that can be used in the agent-based modeling (ABM) applications. This paper considers multiple data sources, including ASHRAE Thermal Comfort DB II and IEA Annex 66 data sets. A case study of an office building is used to present the workflow of DNAS framework expansion, synthetic population generation, and agent-based modeling.

Chandra Putra, Handi↗

A Flexible and Generic Functional Mock-up Unit Based Threat Injection Framework for Grid-interactive Efficient Buildings: A Case Study in Modelica

Grid-interactive efficient buildings (GEBs) have been considered as an important asset to support the power grid reliability by utilizing the demand flexibility offered by GEBs. GEBs are enabled by advances in sensors and controls, and the communication between building equipment, whole buildings, and the grid. The integration of different building technologies and network-based communication system makes GEBs vulnerable to passive threats such as equipment failure and active threats such as cyber-attacks. Modeling and simulation is an effective way to evaluate the impact of threats on the system performance. This paper proposes a generic and flexible threat injection framework for commonly-used building energy simulators such as EnergyPlus and Modelica to support threat modeling and evaluation. This framework leverages functional mock-up unit (FMU) to develop a general modeling interface for threat injection and simulation. A numerical case study using Modelica as a building energy simulator is conducted to demonstrate the capability of the framework for supporting single/multiple-order threat modeling and simulation of a GEB. Four threats and their combinations are injected on a Modelica-based threat-free building energy and control system, including operating supply fan at its full speed, remotely cycling the chiller on and off, blocking the chiller from receiving the chilled water supply temperature setpoints, and hijacking the global zone air temperature setpoint. Simulation results show that the cyber-attack that leads to short-term signal blocking has small effects on the system operation due to the "self-healing" feature of the heating, ventilation, and air-conditioning (HVAC) interactive control system. The threat that takes control of resetting the global zone air temperature setpoints has the most adverse impact on the system energy use, peak power demand, thermal comfort and the provision of demand flexibility. The combination of four threats have aggregative effects on the system but the effects are less than the additive effects of the individual threat.

Fu, Yanyang↗

Analysis of Pre-Retrofit Building and Utility Data

IBACOS analyzed pre-retrofit daily utility data to sort homes by energy consumption, allowing for better targeting of homes for physical audits. Following ASHRAE Guideline 14 normalization procedures, electricity consumption of 1,166 all electric production-built homes' was modeled. The homes were in two communities -- one built in the 1970s and the other in the mid-2000s.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Performance evaluation of radiant cooling system integrated with air system under different operational strategies

The paper describes a parametric study developed to estimate the energy savings potential of a radiant cooling system installed in a commercial building in India. The study is based on numerical modeling of a radiant cooling system installed in an Information Technology (IT) office building sited in the composite climate of Hyderabad. To evaluate thermal performance and energy consumption, simulations were carried out using the ANSYS FLUENT and EnergyPlus softwares, respectively. The building model was calibrated using the measured data for the installed radiant system. Then this calibrated model was used to simulate the energy consumption of a building using a conventional all-air system to determine the proportional energy savings. For proper handling of the latent load, a dedicated outside air system (DOAS) was used as an alternative to Fan Coil Unit (FCU). A comparison of energy consumption calculated that the radiant system was 17.5 % more efficient than a conventional all-air system and that a 30% savings was achieved by using a DOAS system compared with a conventional system. Computational Fluid Dynamics (CFD) simulation was performed to evaluate indoor air quality and thermal comfort. It was found that a radiant system offers more uniform temperatures, as well as a better mean air temperature range, than a conventional system. To further enhance the energy savings in the radiant system, different operational strategies were analyzed based on thermal analysis using EnergyPlus. Lastly, the energy savings achieved in this parametric run were more than 10% compared with a conventional all-air system.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Hood River Passive House

The Hood River Passive Project was developed by Root Design Build of Hood River Oregon using the Passive House Planning Package (PHPP) to meet all of the requirements for certification under the European Passive House standards. The Passive House design approach has been gaining momentum among residential designers for custom homes and BEopt modeling indicates that these designs may actually exceed the goal of the U.S. Department of Energy's (DOE) Building America program to reduce home energy use by 30%-50% (compared to 2009 energy codes for new homes). This report documents the short term test results of the Shift House and compares the results of PHPP and BEopt modeling of the project. The design includes high R-Value assemblies, extremely tight construction, high performance doors and windows, solar thermal DHW, heat recovery ventilation, moveable external shutters and a high performance ductless mini-split heat pump. Cost analysis indicates that many of the measures implemented in this project did not meet the BA standard for cost neutrality. The ductless mini-split heat pump, lighting and advanced air leakage control were the most cost effective measures. The future challenge will be to value engineer the performance levels indicated here in modeling using production based practices at a significantly lower cost.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Resilient cooling through geothermal district energy system

Decarbonization and resilience to heat waves have recently become high priorities for building and district energy systems. Geothermal coupled district heating and cooling systems that operate a water loop near ground temperature gain increasing adoption to support decarbonization. In these systems, vapor-compression machines, distributed in the energy transfer stations, lift the temperature up or down to the needs of the particular building. In principle, these systems can provide low-power, free cooling from the geothermal bore field during heat waves when electricity is often scarce. However, the performance of such a resilience operation mode and its implication on the energy system configuration and the sizing of the bore field and HVAC equipment is not yet understood. Consequently, we are assessing their resilience, power use and design implications under a scenario of a heat wave on five working days during which chillers are switched off to reduce electrical consumption. Our analysis is based on high-fidelity, coupled dynamic models of district energy, building-side HVAC and actual control logic, with whole building energy simulation used to assess thermal conditions in a 2004 vintage multi-zone office building in Chicago, IL. The results show that relying only on waterside economizer cooling, the indoor thermal conditions can be maintained in a tolerable range for the majority of the building zones with half the electrical energy compared to standard chiller operation. Thermal comfort in the hottest zones can be further improved by oversizing the cooling coil. However, the waterside economizer has significant implications on the system configuration and sizing: The geothermal bore field needs to be sized about 30% larger than the upper limit of the range observed for conventional geothermal systems. Nevertheless, if a central chiller plant is added, the bore field can be downsized to the typical design range. The latter configuration still allows compressor-less cooling during the heat wave with peak power reduced by 60% compared to the standard design and chiller operation.

15 GEOTHERMAL ENERGY↗

Final Energy Savings Analysis of the Proposed NYStretch-Energy Code 2018

In 2017, New York State Energy Research and Development Authority (NYSERDA) developed its 2016 Stretch Code Supplement to the 2016 New York State Energy Conservation Construction Code. Since2017, NYSERDA has continued to develop the 2018 edition, as part of the efforts to achieve a statewide Net Zero Energy Code by 2028. To support this effort, Pacific Northwest National Laboratory (PNNL)conducted energy simulation analysis to quantify the energy savings of proposed commercial provisions of the NYStretch-Energy Code 2018 compared to ANSI/ASHRAE/IES1 Standard 90.1-2013. Specifically, PNNL collaborated with New Buildings Institute (NBI), and developed energy-efficiency measures (EEMs) from national model codes and standards, high-performance building codes and standards, regional energy codes, and measures being proposed as part of the ongoing NYStretch-Energy code development process. PNNL analyzed these measures using whole building energy simulation for selected prototype commercial and multifamily buildings representing buildings in New York State.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Final Energy Savings Analysis of the Proposed NYStretch-Energy Code 2018

In 2017, New York State Energy Research and Development Authority (NYSERDA) developed its 2016 Stretch Code Supplement to the 2016 New York State Energy Conservation Construction Code. Since 2017, NYSERDA has continued to develop the 2018 edition, as part of the efforts to achieve a statewide Net Zero Energy Code by 2028. To support this effort, Pacific Northwest National Laboratory (PNNL) conducted energy simulation analysis to quantify the energy savings of proposed commercial provisions of the NYStretch-Energy Code 2018 compared to ANSI/ASHRAE/IES1 Standard 90.1-2013. Specifically, PNNL collaborated with New Buildings Institute (NBI), and developed energy-efficiency measures (EEMs) from national model codes and standards, high-performance building codes and standards, regional energy codes, and measures being proposed as part of the ongoing NYStretch-Energy code development process. PNNL analyzed these measures using whole building energy simulation for selected prototype commercial and multifamily buildings representing buildings in New York State. This report describes the analysis methodology, explains detailed specifications of the EEMs, and summarizes the results of individual EEMs and EEM bundles by building type and climate zone. As shown in Figure ES.1, significant energy saving could be achieved by adopting the NYStretch-Energy Code 2018.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Data and Analytics to Inform Energy Retrofit of High Performance Buildings

Buildings consume more than one-third of the world?s primary energy. Reducing energy use in buildings with energy efficient technologies is feasible and also driven by energy policies such as energy benchmarking, disclosure, rating, and labeling in both the developed and developing countries. Current energy retrofits focus on the existing building stocks, especially older buildings, but the growing number of new high performance buildings built around the world raises a question that how these buildings perform and whether there are retrofit opportunities to further reduce their energy use. This is a new and unique problem for the building industry. Traditional energy audit or analysis methods are inadequate to look deep into the energy use of the high performance buildings. This study aims to tackle this problem with a new holistic approach powered by building performance data and analytics. First, three types of measured data are introduced, including the time series energy use, building systems operating conditions, and indoor and outdoor environmental parameters. An energy data model based on the ISO Standard 12655 is used to represent the energy use in buildings in a three-level hierarchy. Secondly, a suite of analytics were proposed to analyze energy use and to identify retrofit measures for high performance buildings. The data-driven analytics are based on monitored data at short time intervals, and cover three levels of analysis ? energy profiling, benchmarking and diagnostics. Thirdly, the analytics were applied to a high performance building in California to analyze its energy use and identify retrofit opportunities, including: (1) analyzing patterns of major energy end-use categories at various time scales, (2) benchmarking the whole building total energy use as well as major end-uses against its peers, (3) benchmarking the power usage effectiveness for the data center, which is the largest electricity consumer in this building, and (4) diagnosing HVAC equipment using detailed time-series operating data. Finally, a few energy efficiency measures were identified for retrofit, and their energy savings were estimated to be 20percent of the whole-building electricity consumption. Based on the analyses, the building manager took a few steps to improve the operation of fans, chillers, and data centers, which will lead to actual energy savings. This study demonstrated that there are energy retrofit opportunities for high performance buildings and detailed measured building performance data and analytics can help identify and estimate energy savings and to inform the decision making during the retrofit process. Challenges of data collection and analytics were also discussed to shape best practice of retrofitting high performance buildings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Energy and IAQ Implications of Residential Ventilation Cooling

This study evaluates the energy, humidity and indoor air quality (IAQ) implications of residential ventilation cooling in all U.S. IECC climate zones. A computer modeling approach was adopted, using an advanced residential building simulation tool with airflow, energy and humidity models. An economizer (large supply fan) was simulated to provide ventilation cooling while outdoor air temperatures were lower than indoor air temperatures (typically at night). The simulations were performed for a full year using one-minute time steps to allow for scheduling of ventilation systems and to account for interactions between ventilation and heating/cooling systems.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Hood River Passive House, Hood River, Oregon (Fact Sheet)

The Hood River Passive Project was developed by Root Design Build of Hood River Oregon using the Passive House Planning Package (PHPP) to meet all of the requirements for certification under the European Passive House standards. The Passive House design approach has been gaining momentum among residential designers for custom homes and BEopt modeling indicates that these designs may actually exceed the goal of the U.S. Department of Energy's (DOE) Building America program to "reduce home energy use by 30%-50%" (compared to 2009 energy codes for new homes). This report documents the short term test results of the Shift House and compares the results of PHPP and BEopt modeling of the project. The design includes high R-Value assemblies, extremely tight construction, high performance doors and windows, solar thermal DHW, heat recovery ventilation, moveable external shutters and a high performance ductless mini-split heat pump. Cost analysis indicates that many of the measures implemented in this project did not meet the BA standard for cost neutrality. The ductless mini-split heat pump, lighting and advanced air leakage control were the most cost effective measures. The future challenge will be to value engineer the performance levels indicated here in modeling using production based practices at a significantly lower cost.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Occupant behavior models: A critical review of implementation and representation approaches in building performance simulation programs

Occupant behavior (OB) in buildings is a leading factor influencing energy use in buildings. Quantifying this influence requires the integration of OB models with building performance simulation (BPS). This study reviews approaches to representing and implementing OB models in today’s popular BPS programs, and discusses weaknesses and strengths of these approaches and key issues in integrating of OB models with BPS programs. Two of the key findings are: (1) a common data model is needed to standardize the representation of OB models, enabling their flexibility and exchange among BPS programs and user applications; the data model can be implemented using a standard syntax (e.g., in the form of XML schema), and (2) a modular software implementation of OB models, such as functional mock-up units for co-simulation, adopting the common data model, has advantages in providing a robust and interoperable integration with multiple BPS programs. Such common OB model representation and implementation approaches help standardize the input structures of OB models, enable collaborative development of a shared library of OB models, and allow for rapid and widespread integration of OB models with BPS programs to improve the simulation of occupant behavior and quantification of their impact on building performance.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗