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DOE OSTI2022

Impact of model predictive control-enabled home energy management on large-scale distribution systems with photovoltaics

Residential customers use more than one-quarter of the electricity in the world. Optimally managing home energy consumption is an effective way of easing the operational challenges facing the electric grid with increasing solar photovoltaics (PV). This paper studies the impact of the future proliferation of home energy management systems (HEMS) in the presence of PV on large-scale distribution systems. First, we present a stochastic HEMS model that minimizes residential customers' thermal discomfort and energy costs under uncertainty. The HEMS model schedules the optimal operations of residential appliances in the presence of PV within a mixed-integer linear programming-based model predictive control framework that links the proposed HEMS to a quasi-steady-state time-series simulation tool. Additionally, extensive simulations are conducted for a stand-alone residential home using two tariff structures and for 1977 homes on an 8,500-node distribution feeder. Simulation results quantify the impact of the future proliferation of HEMS on the large-scale distribution system with PV.

14 SOLAR ENERGY↗

DOE OSTI2021

Sensitivity Analysis of Occupant Preferences on Energy Usage in Residential Buildings: Preprint

Residential buildings, accounting for 37% of the total electricity consumption in the United States, are suitable for demand-side management (DSM) programs to support effective and economical operation of the power system. A home energy management system (HEMS) enables residential buildings to participate in such programs. It is important to account for occupant preferences in HEMS to ensure occupant satisfaction while participating in DSM programs. For example, people who prefer a higher thermal comfort level are likely to consume more energy. In this study, we used foresee™, a HEMS developed by the National Renewable Energy Lab (NREL), to perform a sensitivity analysis of occupant preferences with the following objectives: minimize utility cost, minimize carbon footprint, and maximize thermal comfort. To incorporate the preferences into the HEMS, the SMARTER method was used to derive a set of weighting factors for each objective. We performed week-long building energy simulations using a model of a home in Fort Collins, Colorado, where there is mandatory time-of-use electricity rate structure. The foreseeTM HEMS was used to control the home with six different sets of occupant preferences. The study shows that occupant preferences can have a significant impact and is important to consider when modeling residential buildings. Results show that the HEMS could achieve energy reduction ranging from 3% to 21%, cost savings ranging from 5% to 24%, and carbon emission reduction ranging from 3% to 21%, while maintaining a low thermal discomfort level ranging from 0.78 K-hour to 6.47 K-hour in a one-week period during winter. These outcomes quantify the impact of varying occupant preferences and will be useful for controlling the electrical grid and developing HEMS solutions.

carbon footprint↗

NASA NTRS1994

Ozone as a laundry agent on orbit and on the ground

Ozone (03), is the strongest commercial oxidizing agent for aqueous systems and may be ideal for space station laundering operations. It can be generated electronically from air in situ. It kills virtually all microorganisms, attacks many organics and inorganics, and breaks down stable ring structures of benzene and related oils when coupled with ultra violet radiation. It cleans and disinfects in cold water without the need for detergent. It leaves no residues. Ozone permits up to 90% wash water recycling and it eliminates wash time, water volume, and recycling problems of a detergent rinse. Ozone is self purging and converts spontaneously to oxygen. It can be rapidly purged by well established catalytic and thermal processes. Scaling of an ozone laundering system for space station may have commercial applications in a consumer model for home use.

Agosto, William N.↗

DOE OSTI2023

Analysis of Building Model Forecasts using Autonomous HVAC Optimization System for Residential Neighborhood

Heating, ventilation, and air conditioning (HVAC) systems account for the highest share of home energy consumption in the United States. Optimized HVAC control can provide thermal improved comfort to the occupants, improve energy efficiency, reduce energy cost, and support grid services. In this paper, we discuss a multi-agent and cloud-based software framework that has been deployed in occupied residential neighborhood. This system enables automatic data collection, learning, optimization, and dispatches signals to neighborhood devices. HVAC optimization is based on model predictive control (MPC). Since the operational performance of MPC depends on model forecasting accuracy, it is crucial to evaluate the model continuously and modify or retrain it as necessary. In this research, we developed an automated workflow to evaluate the performance of temperature and power forecasts based on measured data in the real world. This will provide researchers with a deeper understanding of the model and how it can be improved.

Lebakula, Viswadeep↗

DOE OSTI2022

Building Energy Modeling Enhancements to Identify Least-Cost Pathways to Net-Zero Carbon Homes: Preprint

Residential grid-interactive efficient buildings (GEBs) can utilize high levels of energy efficiency and demand flexibility to deliver value to occupants, the grid, and society. However, without the ability to analyze, design, and optimize residential GEBs there is a risk that homes will not realize their full potential value as efficient and dynamic resources, which could ultimately lead to higher than necessary energy costs for U.S. households and lower realization of potential energy efficiency and demand flexibility benefits such as increased convenience/automation, thermal comfort, durability, indoor air quality, and resilience. In 2018, the National Renewable Energy Laboratory (NREL) Residential Modeling Team developed a vision for an open source Residential GEB Analytics Platform built within DOE's EnergyPlus and OpenStudio modeling environment that would enable the design and optimization of residential GEBs, including the identification of least-cost pathways to highly energy-efficient and energy-flexible homes (e.g., net zero carbon homes). We created a detailed workplan for the development of new and enhanced residential GEB component-level models for EnergyPlus and OpenStudio needed to progress toward the vision for the analytics platform while delivering near-term benefits to industry. This paper 1) presents the vision for the platform, summarizing the workplan for residential GEB modeling enhancements; 2) highlights significant advancements that have been achieved between 2018 and 2022, including stochastic residential occupancy modeling, flexible water heater modeling, detailed lithium-ion stationary battery modeling, and realistic residential HVAC modeling; and 3) outlines ongoing efforts and next steps toward the full vision for the platform.

building energy modeling↗

DOE OSTI2022

Developing a Composite Vacuum Insulated Panel (VIP) Insulation/Vinyl Siding Composite Technology for Retrofitting Residential Walls

This paper reports on a project that has attempted to seize on an opportunity to take a giant leap forward in commercializing a technology that would address a key opportunity to achieve energy savings in the existing residential housing stock. It is typically very difficult to increase the R-value of the walls in existing residential housing as doing so from the inside is disruptive and there have not been good solutions to increase thermal envelope performance from the exterior through adding continuous insulation due to the additional work required to fit existing architectural features to the new wall thickness and to reclad the façade. A high thermal resistivity or R-value per inch product that can be used in these applications offers an excellent solution.This paper summarizes a three-year research project to a produce vacuum insulated panel (VIP)/vinyl siding that would have sufficient R-value to meet the continuous insulation requirements of the 2018 International Energy Conservation Code (IECC, 2018) in all climate zones and has a much thinner profile that will facilitate its application to existing residential homes without the need for expensive retrimming of the architectural details. The paper will supply information on the development of the technology, its thermal modelling, testing, voice of user sessions to solicit input from architects, designers, manufacturers, contractors, and installers, and a techno-economic analysis to gauge its competitiveness with existing product options.

Desjarlais, Andre Omer↗

DOE OSTI2022

Developing a Composite Vacuum Insulated Panel (VIP) Insulation/Vinyl Siding Composite Technology for Retrofitting Residential Walls

This paper reports on a project that has attempted to seize on an opportunity to take a giant leap forward in commercializing a technology that would address a key opportunity to achieve energy savings in the existing residential housing stock. It is typically very difficult to increase the R-value of the walls in existing residential housing as doing so from the inside is disruptive and there have not been good solutions to increase thermal envelope performance from the exterior through adding continuous insulation due to the additional work required to fit existing architectural features to the new wall thickness and to reclad the facade. A high thermal resistivity or R-value per inch product that can be used in these applications offers an excellent solution. This paper summarizes a three-year research project to a produce vacuum insulated panel (VIP)/vinyl siding that would have sufficient R-value to meet the continuous insulation requirements of the 2018 International Energy Conservation Code (IECC, 2018) in all climate zones and has a much thinner profile that will facilitate its application to existing residential homes without the need for expensive retrimming of the architectural details. The paper will supply information on the development of the technology, its thermal modelling, testing, voice of user sessions to solicit input from architects, designers, manufacturers, contractors, and installers, and a techno-economic analysis to gauge its competitiveness with existing product options.

Desjarlais, Andre↗

DOE OSTI2024

Modeling and Analysis of a Heat Pump Clothes Dryer with Thermal Energy Storage

Clothes drying is an energy-intensive process that causes significant electricity consumption and carbon emissions in the US. Approximately 83% of Households in the US own a tumble clothes dryer at home and 80% of dryers are electrical resistance dryers with low energy efficiency. Heat pump technology makes it possible for highly efficient and clean drying. Additionally, the ventless design of heat pump clothes dryers (HPCD) provides more installation flexibility. HPCD involves three primary mediums: wet clothes, a closed air loop, and a refrigerant circuit. The evaporator is used to dehumidify the wet air and the condenser is used to re-heat the dry air. One of the critical technological barriers to HPCD market penetration is its long drying time, primarily due to the relatively low discharging temperature and the slow response during the warm-up period. In this study, the thermal energy storage (TES) technology is adopted to address this challenge by providing pre-heating of air prior to the condenser to increase the operating temperature of the process air. The heat pump will charge the phase change material (PCM) in the TES device with heating energy during clothes washing and the PCM will discharge the stored heat to facilitate air heating during clothes drying. To analyze the optimal design and potential for energy saving and drying time reduction, a mathematical model of the HPCD system was developed. The HPCD is a highly dynamic system with a coupled heat and mass transfer and heat pumping cycle. This paper provides solutions to simulate the transient behavior of the system while maintaining low computational cost. The modeling result indicates reduced energy consumption and drying time by integrating TES with HPCD, as compared to electrical resistance dryers. The study can provide significant insights into improving building flexibility with TES and smart appliances.

Liu, Xiaoli↗

NASA NTRS2013

Development and Implementation of Efficiency-Improving Analysis Methods for the SAGE III on ISS Thermal Model Originating

The Stratospheric Aerosol and Gas Experiment III (SAGE III) instrument is the fifth in a series of instruments developed for monitoring aerosols and gaseous constituents in the stratosphere and troposphere. SAGE III will be delivered to the International Space Station (ISS) via the SpaceX Dragon vehicle in 2015. A detailed thermal model of the SAGE III payload has been developed in Thermal Desktop (TD). Several novel methods have been implemented to facilitate efficient payload-level thermal analysis, including the use of a design of experiments (DOE) methodology to determine the worst-case orbits for SAGE III while on ISS, use of TD assemblies to move payloads from the Dragon trunk to the Enhanced Operational Transfer Platform (EOTP) to its final home on the Expedite the Processing of Experiments to Space Station (ExPRESS) Logistics Carrier (ELC)-4, incorporation of older models in varying unit sets, ability to change units easily (including hardcoded logic blocks), case-based logic to facilitate activating heaters and active elements for varying scenarios within a single model, incorporation of several coordinate frames to easily map to structural models with differing geometries and locations, and streamlined results processing using an Excel-based text file plotter developed in-house at LaRC. This document presents an overview of the SAGE III thermal model and describes the development and implementation of these efficiency-improving analysis methods.

Liles, Kaitlin↗

NASA NTRSDate not supplied

WFIRST CGI: Prism and Polarizer Characterization Modes

As part of its technology demonstration, the WFIRST coronagraph instrument (CGI) will demonstrate point source spectroscopy and polarization measurements of disks. The specific implementation of spectroscopy is a zero-deviation Amici prism and slit to be placed on the planet after high contrast has been achieved by CGI. The polarization optics are a set of Wollaston prisms so that orthogonal polarization states can be measured simultaneously. The CGI spectral characterization mode, being designed and built and Goddard Space Flight Center (GSFC), has a spectral resolution of R50 and is designed to accommodate a 15% bandpass spanning 610-785nm. In order to recover Stokes information, there are two sets of Wollaston prisms clocked 45 degrees with respect to one another with each measurement taken in series. The Wollaston design and optical elements are a contribution by the Japanese Aerospace Exploration Agency, with final alignment and testing being done at GSFC. The spectroscopy mode is designed to target Methane absorption features around 730nm, keeping the spectral resolution as low as possible to improve the signal-to-noise ratio and hence reduce detection time. We highlight the requirements for these modes and address the challenge of on-orbit spectral calibration for a deployable slit in the presence of pointing drifts. Of unique interest is how the observatory error budget couples into good stellar spectrum calibration and subsequent speckle subtraction. We also provide further detail on the optomechanical design, its stability based on thermal and structural predictions, modeled performance, and operations concept. These performance metrics are simulated to demonstrate how a slit located at an arbitrary field point is homed onto the planet and converted to a calibrated spectrum.

Tyler D Groff↗

DOE OSTI2020

Scaling Deep Energy Retrofits for Residential Walls - Energy, Cost, and Economic Assessment of Five Wall Systems

Providing strong economic and performance value is a primary challenge of convincing homeowners to implement deep energy retrofits to their wall systems. This study combines energy modeling and technoeconomic assessment of six experimental residential retrofit wall systems to typical existing homes in cold climates to evaluate their energy performance and cost effectiveness. Deep energy retrofits can significantly improve the energy performance of a home’s thermal envelope, help manage indoor environmental pollutants, increase homeowner comfort, increase building value, and register significant energy and cost savings in the process. We are evaluating exterior wall retrofit components and construction practices to measure and recommend steps to improve financial performance for manufacturers, installers and consumers. This study leverages a literature review, inputs from an advisory group made up of thermal enclosure experts, and simulations to identify state-of-the-art technologies for energy efficient wall systems that are suitable for cold and very cold climate zones. This paper will present results from energy modeling of six experimental wall systems compared to one baseline, that inform cost and energy performance of the subject wall systems.

Ganguli, Sumitrra↗

DOE OSTI2023

Accelerating Adoption of Energy-Efficient Technology with the Thermalize Model

The accelerating impacts of climate change destabilize food systems and ecosystems alongside the communities that rely on them. Thus, climate resilience is a health equity issue at both a physical (relating to biological impacts of pollution and environmental degradation) and a cultural level (loss of subsistence lifestyles, languages, etc). With roughly 20% of US energy-related greenhouse gas emissions stemming from heating, cooling, and powering households, accessible energy-efficient home retrofits are a critical element of climate change mitigation strategies. For communities already producing electricity from renewable sources, like Juneau, incentivizing ductless heat pump upgrades and energy efficiency retrofits provides an accessible pathway to transition households away from oil heating and drastically reduce emissions. Thermalize Juneau is a pilot program that will explore a repeatable framework for accelerating the adoption of energy-efficient technology in Alaska communities. This poster will describe Thermalize Juneau's goals and framework, progress through spring 2021, and future plans.

ductless heat pumps↗

NASA NTRS2007

Reply to "Comment on 'A Self-Consistent Model of the Interacting Ring Current Ions and Electromagnetic Ion Cyclotron Waves, Initial Results: Waves and Precipitation Fluxes' and 'Self-Consistent Model of the Magnetospheric Ring Current and Propagating Electromagnetic Ion Cyclotron Waves: Waves in Multi-Ion Magnetosphere' by Khazanov et al. et al."

It is well-known that the effects of electromagnetic ion cyclotron (EMIC) waves on ring current (RC) ion and radiation belt (RB) electron dynamics strongly depend on such particle/wave characteristics as the phase-space distribution function, frequency, wavenormal angle, wave energy, and the form of wave spectral energy density. The consequence is that accurate modeling of EMIC waves and RC particles requires robust inclusion of the interdependent dynamics of wave growth/damping, wave propagation, and[ particles. Such a self-consistent model is being progressively developed by Khazanov et al. [2002, 2006, 2007]. This model is based on a system of coupled kinetic equations for the RC and EMIC wave power spectral density along with the ray tracing equations. Thome and Home [2007] (hereafter referred to as TH2007) call the Khazanov et al. [2002, 2006] results into question in their Comment. The points in contention can be summarized as follows. TH2007 claim that: (1) "the important damping of waves by thermal heavy ions is completely ignored", and Landau damping during resonant interaction with thermal electrons is not included in our model; (2) EMIC wave damping due to RC O + is not included in our simulation; (3) non-linear processes limiting EMIC wave amplitude are not included in our model; (4) growth of the background fluctuations to a physically significantamplitude"must occur during a single transit of the unstable region" with subsequent damping below bi-ion latitudes,and consequently"the bounce averaged wave kinetic equation employed in the code contains a physically erroneous 'assumption". Our reply will address each of these points as well as other criticisms mentioned in the Comment. TH2007 are focused on two of our papers that are separated by four years. Significant progress in the self-consistent treatment of the RC-EMIC wave system has been achieved during those years. The paper by Khazanov et al. [2006] presents the latest version of our model, and in this Reply we refer mostly to this paper.

Khazanov, G. V.↗

DOE OSTI2020

Development and Evaluation of Occupancy-Aware HVAC Control for Residential Building Energy Efficiency and Occupant Comfort

Occupancy-aware heating, ventilation, and air conditioning (HVAC) control offers the opportunity to reduce energy use without sacrificing thermal comfort. Residential HVAC systems often use manually-adjusted or constant setpoint temperatures, which heat and cool the house regardless of whether it is needed. By incorporating occupancy-awareness into HVAC control, heating and cooling can be used for only those time periods it is needed. Yet, bringing this technology to fruition is dependent on accurately predicting occupancy. Non-probabilistic prediction models offer an opportunity to use collected occupancy data to predict future occupancy profiles. Smart devices, such as a connected thermostat, which already include occupancy sensors, can be used to provide a continually growing collection of data that can then be harnessed for short-term occupancy prediction by compiling and creating a binary occupancy prediction. Real occupancy data from six homes located in Colorado is analyzed and investigated using this occupancy prediction model. Results show that non-probabilistic occupancy models in combination with occupancy sensors can be combined to provide a hybrid HVAC control with savings on average of 5.0% and without degradation of thermal comfort. Model predictive control provides further opportunities, with the ability to adjust the relative importance between thermal comfort and energy savings to achieve savings between 1% and 13.3% depending on the relative weighting between thermal comfort and energy savings. In all cases, occupancy prediction allows the opportunity for a more intelligent and optimized strategy to residential HVAC control.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2021

Model-Based and Data-Driven HVAC Control Strategies for Residential Demand Response

Not Available

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2022

Occupancy-Based Controls for an All-Electric Residential Community in a Cold Climate

In residential buildings, rapid improvements in sensors, communication, and information technology have enabled occupancy-based building controls. These controls utilize occupancy information and modify the operation of the heating, ventilation, and air-conditioning (HVAC) system to minimize excess HVAC energy use, especially when the building is unoccupied. This reduces the total building energy consumption and utility bills while maintaining thermal comfort. In this paper, we present two novel occupancy-driven controls - reactive control and predictive control - and compare their performance. We model an all-electric residential community based on a 27- home community in Basalt, Colorado, in the United States. We simulated various scenarios, considering different temperature setback and control algorithms, to analyze the community-scale impact of these occupancy-based controls. The results show that total HVAC energy savings in a building ranges from 1%- 20% compared to the baseline scenario without occupancy-based controls. The energy-saving potential is highly correlated with the occupancy pattern and temperature setback in the building.

ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION↗

DOE OSTI2022

Occupancy-Based Controls for an All-Electric Residential Community in a Cold Climate: Preprint

ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION↗

DOE OSTI2025

Cool rooms for indoor heat resilience: Evaluating affordable cooling strategies in heat-stressed California homes

Extreme heat conditions pose significant indoor survivability challenges for resource-constrained communities, which often lack access to cooling, have poorly insulated homes, and face compounding socioeconomic vulnerabilities. Moreover, concurrent power outages worsen health risks and heat-related illnesses. It is therefore crucial to develop innovative and affordable cooling approaches to protect vulnerable populations. This study assesses the efficacy of “cool rooms”– a designated space within a home equipped with passive and low-power active cooling measures to maintain safe indoor temperatures during extreme heat events and power disruptions. Using a physics-based building energy modeling approach, we evaluate the efficacy of various retrofit packages in maintaining thermal safety within the cool room under recent extreme heat conditions. The results indicate that passive measures can reduce 64% of hours with unmet standard effective temperatures, while the combination of passive and low-power active measures with built-in batteries further cuts this to 86%. Nevertheless, these strategies remain insufficient to maintain indoor thermal safety during extended outages. In contrast, integrating a solar-powered mini-split heat pump, whose technical potential was evaluated in this study, reduces indoor air temperatures below the 28 °C overheating threshold and significantly improves indoor habitability. The localized cool room strategy also offers potential for grid resilience by reducing peak electricity demand by up to 70% compared to whole house cooling during heat waves. The findings can inform the development of actionable heat mitigation plans and retrofit policies for residential communities with relatively low adoption of air conditioning such as warm marine climates.

Cool room↗