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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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DOE OSTI2017

Simulation Methods for Transactive Energy

Transactive energy is a new approach for managing the electric power distribution system based on principles of economic value, with engineering constraints. This combined approach is well established in the bulk power system, but transactive energy incorporates many more participants and new types of participant, including end-use loads and distributed energy resources. The market mechanisms are new and largely untested, which calls for careful design to avoid unwanted results and behaviors. The supporting simulation platforms must be flexible and multi-disciplinary (market, distribution grid, bulk grid, buildings, appliances, distributed energy resources, communication systems). These platforms make it possible for products to be developed and tested on large realistic models, before deployment into the real world.

load modeling↗

DOE OSTI2017

ResStock - Targeting Energy and Cost Savings for U.S. Homes

The ResStock analysis tool is helping states, municipalities, utilities, and manufacturers identify which home upgrades save the most energy and money. Across the country there's a vast diversity in the age, size, construction practices, installed equipment, appliances, and resident behavior of the housing stock, not to mention the range of climates. These variations have hindered the accuracy of predicting savings for existing homes. Researchers at the National Renewable Energy Laboratory (NREL) developed ResStock. It's a versatile tool that takes a new approach to large-scale residential energy analysis by combining: large public and private data sources, statistical sampling, detailed subhourly building simulations, high-performance computing. This combination achieves unprecedented granularity and most importantly - accuracy - in modeling the diversity of the single-family housing stock.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2017

Synchronous temperature rate control for refrigeration with reduced energy consumption

Methods of operation for refrigerator appliance configurations with a controller, a condenser, at least one evaporator, a compressor, and two refrigeration compartments. The configuration may be equipped with a variable-speed or variable-capacity compressor, variable speed evaporator or compartment fans, a damper, and/or a dual-temperature evaporator with a valve system to control flow of refrigerant through one or more pressure reduction devices. The methods may include synchronizing alternating cycles of cooling each compartment to a temperature approximately equal to the compartment set point temperature by operation of the compressor, fans, damper and/or valve system. The methods may also include controlling the cooling rate in one or both compartments. Refrigeration compartment cooling may begin at an interval before or after when the freezer compartment reaches its lower threshold temperature. Freezer compartment cooling may begin at an interval before or after when the freezer compartment reaches its upper threshold temperature.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2017

DOE Zero Energy Ready Home Case Study: United Way of Long Island, United Veterans Beacon House

United Way of Long Island’s Housing Development Corporation built this 3,719-ft2 two–story, 5-bedroom home in Huntington Station, New York, to the rigorous performance requirements of the U.S. Department of Energy’s Zero Energy Ready Home Program. The home is packed with high-performance features like LED lighting and ENERGY STAR appliances. The asymmetrical, optimally angled roof provides plenty of space for roof-mounted solar panels for electric generation and hot water.

Building America↗

DOE OSTI2017

Energy Saver: Tips on Saving Money & Energy at Home

Provides consumers with home energy and money savings tips such as insulation, weatherization, heating, cooling, water heating, energy efficient windows, landscaping, lighting, and energy efficient appliances.

Energy Savers, Tips, Money, Home, Saver, Consumer↗

DOE OSTI2018

Fast Primary Frequency Response Using Coordinated DER and Flexible Loads: Framework and Residential-Scale Demonstration: Preprint

Methods for supporting grid frequency stabilization using widespread flexible load and DER are becoming essential as the portion of synchronous generation decreases. This article develops a framework for providing fast primary frequency response that leverages deferrable loads and DER coordinated using high-speed measurements in real time to ensure that local objectives are met. The framework is demonstrated in a residential-scale experiment with four household appliances and an inverter. The effectiveness of an example load management algorithm is demonstrated using three underfrequency anomaly test cases. The experimental data corroborates that in all cases, the entire coordinated response, from detection and measurement of a frequency anomaly to completed coordinated net-load response, is completed within 143 ms (about 8.5 cycles).

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2018

Hardware-in-the-Loop (HIL) Simulations for Smart Grid Impact Studies: Preprint

Hardware-in-the-loop (HIL) simulation is increasingly employed in power engineering as more inverter-based generation and smart appliances are connected to the electric grid. HIL techniques allow for co-simulation of analytical models with actual devices whose complex behavior is computationally inefficient or difficult to capture. It also allows for testing of the behavior of these devices under adverse conditions that only occur rarely in the field, but that are important to evaluate. An overview of how HIL simulation has been used to date is provided. This paper further proposes that HIL simulation should play an important role in evaluating new control strategies, especially at the distribution level, that are being proposed to allow for continued affordable and reliable operation of the electric grid with the introduction of these new technologies. It presents a new capability that was developed to enable evaluation of interactions between residential loads and the smart grid: smart home hardware-in-the-loop. The paper includes results from an HIL simulation that incorporates multiple technologies and controls.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2018

Review of Inorganic Salt Hydrates with Phase Change Temperature in Range of 5°C to 60°C and Material Cost Comparison with Common Waxes

Phase change materials (PCMs) with desirable phase change temperatures can be used to provide a constant temperature thermal source or sink for diverse applications. As such, incorporating PCMs into building materials, equipment, or appliances can shift and/or reduce the energy load. The motivation of this work is to identify low-cost inorganic salt hydrate PCMs that can complement current building systems and designs, and compare them with common paraffins.In this work, we analyzed inorganic salt hydrates with phase change temperatures in the range of 5-60°C, to target both space heating and cooling applications. The properties of the salt hydrates were compared with paraffins over the same temperature range. The results showed that PCMs with a melting temperature above 20°C, salt hydrates have advantages over paraffins including higher thermal energy density (45-120 kWh/m3 for salt hydrates; 45-60 kWh/m3 for paraffins) and generally lower material energy cost (1-20 $/kWh for salt hydrates; 20-30 $/kWh for comparable paraffins). For PCMs with a melting temperature less than 20°C, the material cost is higher for both salt hydrates and paraffins (30-110 $/kWh for both classes of materials) and salt hydrates retain their advantage of greater thermal energy density (50-120 kWh/m3 for salt hydrates; 45-60 kWh/m3 for paraffins). In all cases, factors including thermal cyclability, stability, congruency, corrosion, and supercooling must be considered when comparing paraffins and salt hydrates for a particular application. Finally, we give an overview of enhancement techniques for salt hydrate PCMs and find that limited efforts have been pursued to tune salt hydrate phase change temperatures, with a wider range of studies investigating stabilization and minimization of supercooling. This analysis shows the potential of developing salt hydrate PCMs for low-cost heating and cooling thermal energy storage systems for a range of applications.

Hirschey, Jason↗

DOE OSTI2018

Stochastic Model Predictive Control for Demand Response in a Home Energy Management System: Preprint

This paper presents a chance constrained, model predictive control (MPC) algorithm for demand response (DR) in a home energy management system (HEMS). The HEMS optimally schedules controllable appliances given user preferences such as thermal comfort and energy cost sensitivity, and available residentially-owned power sources such as photovoltaic (PV) generation and home battery systems. The proposed control architecture ensures both the DR event and indoor thermal comfort are satisfied with a high probability given the uncertainty in available PV generation and the outdoor temperature forecast. The uncertainties are incorporated into the MPC formulation using probabilistic constraints instead of computationally limiting sampling-based approaches. Simulation results for various user preferences and probabilistic model parameters show the effectiveness of the HEMS algorithm response to DR requests.

47 OTHER INSTRUMENTATION↗

DOE OSTI2018

Computing erasure metadata and data layout prior to storage using a processing platform

Techniques are provided for computing data and metadata layout prior to storage in a storage system using a processing platform. An exemplary processing platform comprises one or more of a compute node and a burst buffer appliance. The processing platform communicates with a plurality of the compute nodes over a network, wherein a plurality of applications executing on the plurality of compute nodes generate a plurality of data objects; computes erasure metadata for one or more of the data objects on at least one of the compute nodes; and provides the erasure metadata with the corresponding one or more data objects to a storage system. The processing platform optionally determines a full set of the data objects to be stored and queries the storage system to determine an anticipated layout of the full set of the data objects to be stored. The anticipated layout allows special handling, for example, for small files and large files that are identified based on predefined criteria.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

DOE OSTI2019

Evaluating the Impact of Price-Responsive Load on Power Systems Using Integrated T&D Simulation: Preprint

This paper explores the advantages and challenges of simulating price-responsive load (PRL) interactions with large-scale power systems using integrated transmission and distribution (T&D) models. This analysis uses the Integrated Grid Modeling System (IGMS) software to capture 'ISO-to-appliance' simulations using a synthetic T&D model built on the PJM 5 Bus transmission network with multiple full-scale taxonomy feeders that include physics-based models of thousands of PRLs. The results show substantial differences in the impacts of PRLs between integrated T&D and transmission-only (T-only) models. Similarly differences are observed between the price response of individual distribution feeders and the corresponding transmission bus in the integrated T&D simulations, which cannot be captured in T-only simulations. Experiments include both traditional price responsive load reductions and price-driven load increases during low net demand periods driven by high daytime generation from distributed generation-based photovoltaics (DGPV).

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2017

DOE Zero Energy Ready Homes

This article describes the U.S. Department of Energy's Zero Energy Ready Home Program and Housing Innovation Awards. Since 2013, builders around the country have certified over 1,170 homes to the high performance criteria of the DOE Zero Energy Ready Home program. Each year DOE recognizes the best innovators among this group with the DOE Housing Innovation Awards. 2017 winners will be announced at an awards event taking place at the Energy & Environmental Building Alliance (EEBA) high-performance home summit October 10-12, 2017, in Atlanta, Georgia. Twenty-five builders are expected to take home awards and grand award winners in each of the five competition categories will be revealed at the conference. Participating builders represent every climate zone in the country and DOE Zero Energy Ready labeled homes can be found in 34 states. Homes represent the full spectrum of the U.S. construction industry, from affordable to production to custom homes and from single-family detached to duplexes and up to five-story multifamily buildings as well as some retrofit projects have also met the criteria. Every DOE ZER certified home is certified through the ENERGY STAR Certified Homes (Version 3.0, revision 8) program and the U.S. Environmental Protection Agency’s Indoor airPLUS program. Each home must meet the hot water distribution requirements of the EPA’s WaterSense program and the insulation requirements of the 2012 International Energy Conservation Code. If the home has HVAC ducts, they must be installed within the conditioned space of the home. Appliances, exhaust fans, ceiling fans, and most of the lighting should be ENERGY STAR qualified. The DOE Zero Energy Ready Home program also requires homes to have solar electric panels installed or at a minimum to have the conduit and electrical panel space in place for future PV installation, if the home is in a location appropriate for solar power. Homes are constructed with enough energy efficiency built in so that, with a reasonable amount of solar PV panels (i.e., small enough to fit comfortably on the roof), the home could produce enough of its own power to equal the power it uses in a year.

U.S. Department of Energy Building Technologies Pr↗

DOE OSTI2019

Real-time forecasting of electricity demand in a streams-based architecture with applications

A streams platform is used. Multiple streams of electricity usage data are received, each from an electrical meter providing periodic updates to electrical usage for devices connected to the electrical meter. Weather information is received corresponding to locations where the electrical meters are. Real-time predictive modeling of electricity demand is performed based on the received multiple streams of electricity usage data and the received weather information, at least by performing: updating a state space model for electrical load curves using the usage data from the streams and the weather, wherein the updating uses current load observations for the multiple streams for a current time period; and creating forecast(s) for the electricity demand. The forecast(s) of the electricity demand are output. Appliance-level predictions may be made and used, and substitution effects and load management functions may be performed.

Ghosh, Soumyadip↗

DOE OSTI2019

High-Frequency, Multiclass Nonintrusive Load Monitoring for Grid-Interactive Residential Buildings: Preprint

Smart buildings with net-load metering and control capabilities can provide valuable flexibility to grid operators. This article develops a novel approach for high-frequency, multiclass nonintrusive load monitoring (NILM) that enables effective net-load monitoring capabilities with minimal additional equipment and cost. Relative to existing NILM work, the proposed solution operates at a faster timescale, providing accurate multiclass state predictions for each 60-Hz ac cycle without relying on event-detection techniques. The approach is validated using a test bed with residential appliances and shown to have high accuracy, good generalization properties, and sufficient response time to support building grid-interactive control at fast timescales relevant to the provision of grid frequency support services.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2019

Seminar 13 - Advanced Methods for Grid Integration of High-Performance Residential Communities

High-performance residential communities such as net-zero energy (NZE) and NZE-ready communities are emerging across the United States as many cities and states have committed to achieve ambitious energy efficiency and renewable energy goals between now and 2050. The achievement of these goals will transform the nation's communities into the holistic paradigms consisting of pervasive solar photovoltaics (PVs) and other renewable distributed energy resources, energy storage and flexible loads. However, integrating residential communities with high PV penetration may bring many challenges to the grid. For example, during many hours of the year, electric power is flowing out of PV-enabled homes and back into the grid. When this happens simultaneously in many nearby homes, distribution feeder voltage can be raised significantly. Intermittent solar power can also cause voltage flickers, leading to potential damages on both distribution feeder and home appliances. Existing solutions, such as PV curtailment, battery storage, and direct load control, are not able to address all the challenges in a cost-effective way. Better understanding is needed on how to deploy rooftop PV, how to predict building loads, and how to coordinate the homes in a community to enhance grid reliability. This seminar consists of four integral presentations that cover different aspects of a solution to these challenges. First, we will present an automated method to identify the best surfaces to deploy PV and size PV according to the PV penetration goals in a community. Second, we will present a streamlined way to create gray-box building models that are suitable for large-scale building-grid co-simulation. Next, we will present a data-driven method to estimate the end-use energy consumption to better coordinate the behind-the-meter resources to reduce utility cost, provide grid services, and improve renewable energy integration. Lastly, we will present a hierarchical control system that integrates the building models and the estimated non-dispatchable loads into the decision-making process to enhance the reliability and resilience of the residential community. Simulation results from an NZE-ready community in Fort Collins, Colorado will be presented in all four presentations and the guidelines on better grid integration of residential communities will be provided.

14 SOLAR ENERGY↗

DOE OSTI2019

Permanent Electrical Loads in New Homes

Numerous electrical products and components are installed by the builder during construction and prior to occupancy. Some of these components are required by safety codes, such as smoke detectors, others are needed to support the communications infrastructure, and still others provide features that future occupants will find useful, such as remotely controlled garage door openers. We compiled a list of over 50 builder-installed devices that are likely to have continuous power consumption, and measured the power consumptions for a smaller group. A procedure to measure these loads in a home was developed based on readings from the smart meter. A typical American home can easily have 80 W of continuous power – over 650 kWh/year – devoted to these components. New homes are likely to have more of these devices and higher loads. Techniques to reduce this energy use include: selection of lowest-power solutions when a range of power consumptions are available, more efficient circuitry and power management, a separate DC circuit to serve DC-powered appliances, and use of energyscavenging sensors and controls in place of grid-powered components. A protocol to define and measure builder-installed loads, along with a recommended ceiling, might also stimulate savings.

Meier, Alan↗

DOE OSTI2020

High-Frequency, Multiclass Nonintrusive Load Monitoring for Grid-Interactive Residential Buildings

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2020

Machine-Learning-Driven, Site-Specific Weather Forecasting for Grid-Interactive Efficient Buildings: Preprint

Emerging grid-interactive efficient buildings (GEBs) have great potential to provide much-needed demand flexibility to electric grids while fulfilling their own control targets by co-optimizing smart appliances, solar photovoltaics, electric vehicles, and energy storage at buildings. To enable the optimal operation of GEBs, site-specific weather information—such as temperature, solar irradiance, relative humidity, and wind speed—is crucial; however, this information is generally unavailable or expensive to obtain. This paper develops advanced machine learning methods to provide precise weather forecasts for individual building sites using readily available weather station data. Support vector regression and artificial neural networks have been employed to learn the spatiotemporal correlations between the weather conditions at nearby weather stations and the individual building site. The proposed site-specific weather forecasting methods have been validated using 1-year actual weather measurement data collected in the Denver metro area. Results show that the developed machine-learning-driven methods can accurately forecast the temperature at the target building site 1 hour ahead with mean absolute error less than 0.72°C and a 48% improvement over the persistence method. Site-specific weather forecasts will improve the understanding of the microclimate effect and its impact on building energy consumption. This information will drive efficiency upgrades and adjustments of building control strategies to improve energy savings and increase flexibility in building loads.

30 DIRECT ENERGY CONVERSION↗