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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS1976

Experimental solar heating-cooling system model tests of a full-scale building system

An experimental solar heating and cooling system model has been built and operated, combining elements that are programmable - heating and/or cooling load of a building, collected solar energy - with experimental equipment. The system model was based on the loads and components used in the Solar Building Test Facility (SBTF) which includes a 1394 square meter solar collector field, at NASA-Langley. Operations covered 5 continuous days under summer conditions. For the system model, up to 55% of the simulated collected solar energy was used for the building load. This amount constituted 35% of the building cooling load. Heat loss was significant. If tank heat loss were eliminated, 75% of the collected solar energy would be used. This amount would supply approximately 50% of the building cooling load.

Namkoong, D.↗
NASA NTRS1976

Tests of a reduced-scale experimental model of a building solar heating-cooling system

An experimental solar heating and cooling system model has been built and operated, combining elements that are programmable (e.g., heating and cooling load of a building and collected solar energy) with experimental equipment. The experimental system model was based on the loads and components used in the Solar Building Test Facility (SBTF), which includes a 1394 sq m solar collector field at NASA Langley. These tests covered 5 continuous days under summer conditions. For the system model up to 55 percent of the simulated collected solar energy was used for the building load. This amount of solar energy supplied 35 percent of the building cooling load. Heat loss was significant. If tank heat loss were eliminated, which would make it similar to the actual SBTF, 75 percent of the collected solar energy would be used. This amount would supply approximately 50 percent of the building cooling load. A higher fraction of solar energy is possible with a more performance-optimized system.

Namkoong, D.↗
DOE OSTI2024

Design Heating and Cooling Load Calculation Versus Building Load Simulation for Cold Climate Heat Pumps: Understanding the "Gap"

This report explores the differences between Manual J-equivalent block load calculations and building HVAC energy simulation results using EnergyPlus™ calculations when designing cold climate heat pump systems for residential use. This study will help HVAC researchers and advanced designers understand the impacts of oversizing heat pumps on home energy use.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Simulation-based assessment on stochastic load scheduling for building cooling systems

Here, to fill knowledge gaps related to stochastic load scheduling, we performed a comprehensive evaluation of the stochastic load scheduling for building cooling systems. Specifically, we studied the common uncertain variables in the load scheduling process for building cooling systems and categorized those variables based on their dynamic patterns. We then developed a generic stochastic load scheduling framework and applied it to building cooling systems that served a simulated community. This community consists of 100 heterogeneous houses and serves as a virtual testbed for evaluating the performance of stochastic load scheduling. In this evaluation, we considered representatives of uncertain variables with different dynamic patterns and included 100 realizations of the considered uncertainty in the evaluation to better catch the probability distribution of the control performance. The evaluation results suggest that deterministic load scheduling can reduce the operating energy cost by 18% but its performance can be affected by uncertainty. Stochastic load scheduling can further decrease the operating energy cost under uncertainty compared to deterministic load scheduling. We also found that the effectiveness of stochastic load scheduling in handling uncertainty is not directly associated with the number of uncertainty scenarios that are considered in its formulation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1979

The updated algorithm of the Energy Consumption Program (ECP): A computer model simulating heating and cooling energy loads in buildings

The energy Comsumption Computer Program was developed to simulate building heating and cooling loads and compute thermal and electric energy consumption and cost. This article reports on the new additional algorithms and modifications made in an effort to widen the areas of application. The program structure was rewritten accordingly to refine and advance the building model and to further reduce the processing time and cost. The program is noted for its very low cost and ease of use compared to other available codes. The accuracy of computations is not sacrificed however, since the results are expected to lie within + or - 10% of actual energy meter readings.

Lansing, F. L.↗
DOE OSTI2020

Deep Reinforcement Learning for Residential HVAC Control with Consideration of Human Occupancy

The Artificial Intelligence (AI) development described herein uses model-free Deep Reinforcement Learning (DRL) to minimize energy cost during residential heating, ventilation, and air conditioning (HVAC) operation. Building cooling loads and HVAC operation are difficult to accurately model due to complexity, lack of measurements and data, and model specific performance, so online machine learning is used to allow for real-time readjustment in performance. Energy costs for the multi-zone cooling unit shown in this work are minimized by scheduling on/off commands around dynamic prices. By taking advantage of precooling events that take place when the price is low, the agent is able to reduce operational cost without violating user comfort. The DRL controller was tested in simulation where the learner achieved a 43.89% cost reduction when compared to traditional, fixed-setpoint operation. The system is now ready for the next phase of testing in a live, real-time home environment.

Mckee, Evan↗
DOE OSTI2025

University of Hawai‘i, Shallow Geothermal Resources: Energy Technology Innovation Partnership Project (Final Report)

Scientists at Lawrence Berkeley National Laboratory (Berkeley Lab) have teamed up with the University of Hawai‘i at Manoa (UH Manoa) through the U.S. Department of Energy’s Energy Technology Innovation Partnership Project to evaluate the technological and market feasibility of shallow geothermal heat exchanger (GHE) technology. UH requested this analysis to evaluate opportunities in building cooling, energy efficiency, and emissions reduction applications in Hawai‘i. UH has an abundance of geologic and geothermal data and is looking to the national labs’ expertise to execute this analysis. UH is also interested in investigating policy, regulatory, and business conditions advantageous for implementation of a pilot project and more broad deployment of this technology in Hawai‘i. In many locations around the world, the demands for heating and cooling are roughly balanced over the course of the year, so GHEs do not cause significant long-term changes in subsurface temperature. This is not the case in Hawai’i, where the demand for heating is very small, meaning that, over time, GHEs will add heat to the subsurface. If temperatures increase significantly, GHE systems will not work as designed. Regional groundwater flow has the potential to sweep heated water away from boreholes, thereby maintaining the functionality of the GHE system. Significant regional groundwater flow requires two things: a sufficiently large driving hydraulic head gradient (usually closely related to surface topography), and sufficient porosity and permeability to enable groundwater to flow in large enough quantities to enable near-borehole temperatures to be maintained at ambient values. Hawai‘i’s volcanic terrain offers ample surface topographic variation. The lava itself shows an extremely large range of porosity and permeability, so sites with large enough values of these properties must be selected. Numerical modeling of coupled groundwater and heat flow can be used to determine how large is large enough. Primarily, closed-loop systems have been investigated. Other options considered are open-loop systems and using cool seawater as the chilling source. Project work investigated the feasibility of GHE technology at two scales. At the island scale, GIS layers of various attributes relevant for GHE were combined to develop an overall favorability map for employing GHE in Hawai‘i. At the local scale, a hydrogeologic model for the subsurface component of a closed-loop system was developed for the Stan Sheriff Center at the UH Manoa campus. This site is considered promising because the rock below and immediately downgradient of the borefield is highly permeable, consisting of a subsurface karst system (limestone containing high-permeability open channels), which is underlain by a thick, high-permeability fractured basalt. Moreover, the site is near the base of the Ko‘olau Range, providing a large hydraulic head gradient. Thus, groundwater flow through the site is expected to be large, enabling efficient removal of heated groundwater. A full-GHE-system model of the site was also developed, with a simplified representation of the subsurface, in which groundwater flow is not considered and heat transfer is purely by conduction. Using the building cooling load data provided by UH, simulation results show that with groundwater flow present, a GHE can operate successfully for at least 10 years, but with no groundwater flow, the subsurface begins to heat up after only one year of operation, making the GHE unviable within 2-6 years. The team also developed a techno-economic model for this site to compare the cost of cooling using a GHE system with the costs of operating the current air-conditioning system. The GHE system is advantageous economically if favorable tax incentives and interest rates can be obtained.

15 GEOTHERMAL ENERGY↗
DOE OSTI2021

Cost-Optimized Cold Climate Heat Pump Development and Field Test

Cold climate heat pumps (CCHPs) expand the heat pump market to climates where heating demand is dominant. They can achieve more than 70% energy savings compared with electric resistance heating and operate at lower cost than using tank-stored propane to fuel a furnace. A high-efficiency heat pump with a heating seasonal performance factor (HSPF)—as defined by the Air-Conditioning, Heating, and Refrigeration Institute (AHRI 2008)—greater than 10.0 would be more efficient than gas heating in terms of source energy. However, developing a cost-effective CCHP involves some challenges. A typical single-speed, air-source heat pump (ASHP) with an HSPF of 7.7 Btu/Wh does not work well under cold outdoor temperature conditions typical of cold climate locations for four major reasons: 1. Discharge temperature is too high—The low suction pressure and high compression pressure ratio at low ambient temperatures causes high compressor discharge temperatures in excess of the maximum limit for many of the compressors on the market. Furthermore, system charge of a heat pump is usually optimized in the cooling mode, which leads to overcharge conditions in the heating mode, further increasing the discharge temperature. 2. Heating capacity is insufficient if sized to meet the building design cooling load— Heating capacity of a single-speed heat pump decreases with ambient temperature. The heating capacity at -13°F (-25°C) typically decreases to 20%–40% of the rated heating capacity at 47°F (8.3°C) (~equivalent to the rated cooling capacity at 95°F [35°C]). Therefore, a single-speed heat pump, typically sized to match the building design cooling load, cannot provide adequate heating capacity to match the building heating load at low ambient temperatures. The capacity deficit is filled by inefficient resistance heat, thus lowering the system efficiency and significantly increasing power demand. 3. Cyclic loss is significant if sized to meet the building design heating load—If a single-speed heat pump is sized to meet the heating load, it will be significantly oversized relative to the cooling load in many cold climates. This will cause excessive on/off cyclic loss during the cooling and heating operations at moderately low ambient temperatures. Thus, capacity modulation capability (e.g., using a variable-speed or multi-stage compressor) is necessary for a CCHP, which uses its full capacity to meet the peak heating load and partial capacity to meet the cooling and part-load heating loads. 4. Coefficient of performance (COP) is low—Heating COP degrades significantly at low ambient temperatures owing to the large temperature difference between the heat source and sink. A target CCHP should be sized to meet the building design heating load while minimizing the cyclic loss for the cooling and heating operations at moderate ambient temperatures.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Building thermal load prediction through shallow machine learning and deep learning

Building thermal load prediction informs the optimization of cooling plant and thermal energy storage. Physics-based prediction models of building thermal load are constrained by the model and input complexity. In this study, we developed 12 data-driven models (7 shallow learning, 2 deep learning, and 3 heuristic methods) to predict building thermal load and compared shallow machine learning and deep learning. The 12 prediction models were compared with the measured cooling demand. It was found XGBoost (Extreme Gradient Boost) and LSTM (Long Short Term Memory) provided the most accurate load prediction in the shallow and deep learning category, and both outperformed the best baseline model, which uses the previous day's data for prediction. Then, we discussed how the prediction horizon and input uncertainty would influence the load prediction accuracy. Major conclusions are twofold: first, LSTM performs well in short-term prediction (1 h ahead) but not in long term prediction (24 h ahead), because the sequential information becomes less relevant and accordingly not so useful when the prediction horizon is long. Second, the presence of weather forecast uncertainty deteriorates XGBoost's accuracy and favors LSTM, because the sequential information makes the model more robust to input uncertainty. Training the model with the uncertain rather than accurate weather data could enhance the model's robustness. Finally, our findings have two implications for practice. First, LSTM is recommended for short-term load prediction given that weather forecast uncertainty is unavoidable. Second, XGBoost is recommended for long term prediction, and the model should be trained with the presence of input uncertainty.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Analysis of Space-Conditioning Loads in Commercial Buildings

Space conditioning end-uses, which include heating, cooling, and ventilation, represent a significant fraction of commercial building energy use, with a wide variety of heating and cooling technology options available in the market. In the interest of improving the overall efficiency of heating, ventilation and air-conditioning (HVAC) technologies, governments, utilities and private sector entities have implemented a variety of market transformation policies that aim to influence consumer purchase decisions. To evaluate the costs and benefits of such programs, analysts typically postulate a hypothetical default equipment choice, and compare it to one that provides comparable service with lower energy and/or power use. The corresponding reduced operating cost provides a benefit that offsets the potential higher cost of improved efficiency. Typically, life-cycle cost or cash-flow analyses are used to quantify the net economic benefit. These analyses require the capability to assess how a given equipment design would perform across a broad range of characteristics, both of the building and of the local weather. While these assessments can be performed using customized building simulations, it is generally not practical to develop and validate detailed building simulation code to cover all the potential variations of equipment design and installation. An alternative, and somewhat simpler, approach is to solely use detailed building simulations to generate time series of heating and cooling loads in commercial buildings. These loads can then be used as input to more detailed, stand-alone engineering models that simulate HVAC system performance under different equipment designs. This approach was used to evaluate a range of high-efficiency commercial packaged air conditioner design options for the Department of Energy’s Appliance and Equipment Standards Program (DOE-EERE 2015). While there may be some loss of precision relative to full simulation, the accuracy of this approach is sufficient for practical applications of cost-benefit analysis. This report describes the development of a database of commercial building heating and cooling loads, generated using the EnergyPlus software package, a whole building energy use model supported by the Department of Energy (DOE-EERE 2020a). EnergyPlus takes as input a set of configuration files that describe the building itself (size, zoning, envelope characteristics, etc.) and the various systems within it (HVAC, lighting, water heating, etc.). This analysis uses a publicly available collection of commercial reference buildings (CRB), comprised of sixteen building types and three vintages (DOE-EERE 2020b; Deru et al 2011). Each building is simulated in eighteen different locations, covering a wide range of climatic conditions. The prototype building description files assign the type of HVAC equipment used, and capacities across climate zones.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Overall chilled water system energy consumption modeling and optimization

The emergence of increasingly affordable variable-speed drive technology has changed the approach used to control chilled water systems equipped with these drives. The purpose of this research was to develop an integrated chilled water modeling technique that can determine the optimal system setpoints and estimate the energy saving potential of chiller system. The chiller system equipped with Variable Frequency Drives (VFDs) on cooling tower fans and condenser water pumps. To accomplish the objective, physical component models of the centrifugal chiller, cooling tower and condenser water pump were established with the goal of incorporating the system’s condenser water flow rate and cooling tower fan speeds as optimization variables. Furthermore, a cooling load prediction algorithm was developed using a multiple non-linear regression model to approximate the building’s cooling load subject to a range of environmental conditions. The inputs and outputs of the individual component models were linked to estimate how adjusting the cooling tower fan and condenser water pump speed would influence the system’s comprehensive performance. Here, the overall system model was then optimized using a generalized reduced gradient optimization algorithm to determine the potential energy savings through speed control with VFDs and to ascertain a control logic strategy for the building automation system to operate the heating and cooling system. A case-study was performed on a single chiller system at a museum and the model was calibrated according to logged data collected over four months. Results showed that for the system analyzed, the energy saving of optimizing the cooling tower fan system was found to be 12–15%, while the energy saving potential of optimizing the condenser water pump with the cooling tower fan was negligible. Additionally, comparing different cooling tower fan control strategies showed that a wet-bulb approach-based cooling tower control strategy was shown to have the highest correlation to the optimized fan speed with an R 2 of 0.924.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1978

JPL Energy Consumption Program (ECP) documentation: A computer model simulating heating, cooling and energy loads in buildings

The engineering manual provides a complete companion documentation about the structure of the main program and subroutines, the preparation of input data, the interpretation of output results, access and use of the program, and the detailed description of all the analytic, logical expressions and flow charts used in computations and program structure. A numerical example is provided and solved completely to show the sequence of computations followed. The program is carefully structured to reduce both user's time and costs without sacrificing accuracy. The user would expect a cost of CPU time of approximately $5.00 per building zone excluding printing costs. The accuracy, on the other hand, measured by deviation of simulated consumption from watt-hour meter readings, was found by many simulation tests not to exceed + or - 10 percent margin.

Lansing, F. L.↗
DOE OSTI2023

Thermochromic Halide Perovskite Windows with Ideal Transition Temperatures

Abstract Urban centers across the globe are responsible for a significant fraction of energy consumption and CO 2 emission. As urban centers continue to grow, the popularity of glass as cladding material in urban buildings is an alarming trend. Dynamic windows reduce heating and cooling loads in buildings by passive heating in cold seasons and mitigating solar heat gain in hot seasons. Here, reduced energy consumption in highly glazed buildings in a mesoscopic building energy model is demonstrated when thermochromic windows are employed. Savings are realized across eight disparate climate zones of the United States. The model is used to determine ideal critical transition temperatures of 20–27.5 °C for thermochromic windows based on metal halide perovskite materials. Ideal transition temperatures are realized experimentally in composite metal halide perovskite films composed of perovskite crystals and an adjacent reservoir phase. The transition temperature is controlled by cointercalating methanol, instead of water, with methylammonium iodide and tailoring the hydrogen‐bonding chemistry of the reservoir phase. Thermochromic windows based on metal halide perovskites represent a clear opportunity to mitigate the effects of energy‐hungry buildings.

14 SOLAR ENERGY↗
DOE OSTI2023

Component-Level Analysis of Heating and Cooling Loads in the U.S. Residential Building Stock

The residential building sector accounts for a substantial portion of total energy consumption in the United States and offers a significant opportunity for energy reduction and decarbonization through improvements in energy efficiency. Heating and air conditioning are the primary contributors to residential energy usage and electricity system peak demand. However, due to the diversity of the housing stock and the complexity of factors affecting heating and cooling demand, identifying the relative contributions to heating and cooling loads poses challenges. To address this, we applied the ResStock analysis tool to simulate 550,000 building energy models, providing statistical representation of residential buildings in the contiguous United States. We introduced outputs that quantified the heating and cooling influence of different components of a home, such as air leakage, envelope components (ceilings, walls, windows, foundations), internal heat gains from people, lighting, plug loads, and duct losses and gains. Leveraging the granularity of ResStock, we present a dataset to enable deeper understanding of the contributors to heating and cooling loads as a function of housing characteristics such as location, envelope efficiency, and building type. This work aims to support prioritization of research and development and informed decision-making for residential building decarbonization.

building simulation↗
DOE OSTI2020

Optimizing PCM-integrated walls for potential energy savings in U.S. Buildings

Buildings in the United States account for nearly half of total U.S. energy use. The energy used for space conditioning can be reduced by utilizing thermal energy storage, such as phase change materials (PCMs), into building envelopes; however, the energy savings of PCM-integrated building envelopes reported in the literature vary widely. In the absence of established guidelines, thermophysical requirements of an optimal PCM, its method of application into the building envelope, and the corresponding energy savings under various climates remain unknown. Here, we perform an extensive numerical investigation on the integration of PCM into building walls to establish the key conditions required for effective utilization of PCM in reducing heat gains in the cooling season and heat losses in the heating season. We also determine the optimal transition temperature, optimal PCM location in the wall, and the energy-saving potential of the PCM-integrated building walls in five U.S. cities located in different International Energy Conservation Code climate zones. Results show that employing PCMs in building walls does not always lead to an improvement; in fact, incorrect applications of PCMs can substantially increase energy use in the buildings. In the climates we studied, PCMs were found effective in reducing heat gains during the cooling season while mostly ineffective in managing heat losses during heating season. Depending on the climate, optimized PCMs in U.S. building walls can provide reduction in the annual heat gain in the range of 3.5% to 47.2% and the annual heat loss in the range of -2.8% to 8.3%. Future consideration of buildings with substantial solar gains in winter may lead to more reduction in heat losses by PCMs.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Cold-Climate Packaged Heat Pumps - Resistance is Futile

The U.S. currently has a large market for room/zonal space conditioning equipment focused primarily on cooling, namely packaged terminal air conditioners (PTACs), packaged terminal heat pumps (PTHPs), and room air conditioners. This equipment largely relies on electric resistance for heating, particularly when outdoor temperatures fall to 40°F or below, presenting a compelling opportunity for energy savings and carbon reductions from reverse cycle heating. This paper provides an overview of cold climate packaged heat pump technologies in the market capable of high output down to outdoor temperatures of 5°F and identifies the technological and market barriers to adoption. For state-of-the-art cold climate packaged heat pumps sold in the retrofit market, defrost meltwater management is the principal barrier to implementation. An energy use analysis is conducted on state-of-the-art cold climate packaged heat pumps for heating and cooling loads by building vintage and climate zone. Potential solutions to defrost meltwater are proposed and modeled for their impact on heating energy efficiency. A national impact assessment estimates the aggregate energy savings and carbon reductions if cold climate packaged heat pumps were to replace existing PTACs and PTHPs in the U.S. building stock. A national, two-track approach is proposed for increasing market adoption in the replacement and new construction markets.

ACEEE Summer Study, cold climate, heat pumps, ccph↗