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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Energy flexibility of residential buildings: A systematic review of characterization and quantification methods and applications

With building electric demand becoming increasingly dynamic, and a growing percentage of intermittent renewable power generation from solar photovoltaics and wind turbines, the power grid is facing increasing challenge to manage the real time balance between the supply and demand. With advancements in smart sensing and metering, smart appliances, electric vehicles, and energy storage technologies, demand side management of residential buildings can help the grid to improve stability by optimizing flexible loads. This paper reviews recent studies on residential building demand side management, with a focus on characterization and quantification of energy flexibility covering various types of flexible loads, metrics, methods, and applications. The reviewed studies showed four levels of applications: building level (45%), district or community level (29%), system level (19%), and building sector level (7%). Shifting loads is the dominant flexibility type in 60% of applications, followed by shedding (19%), generation (16%), and modulating (6%). Depending on the technology and application scope, flexible operations have a wide range of performance, with peak power reductions of 1%~65%, energy savings up to 60%, operational cost reduction of 1%~48%, and greenhouse gas emission reductions of up to29%. More than half (51%) of the studies employed control strategies to achieve flexibility; among those 72% used optimal controls, while 28% used rule-based controls. About 58% of the studies used mathematical formulation to quantify energy flexibility. Most studies were based on simulation, while less than 15% of the studies had measurements from experiments or field tests. The review reveals research opportunities to address significant gaps in the existing literature: (1) establishing a common definition and performance metrics for energy flexibility of buildings that are technology and application agnostic, (2) developing an ontology to standardize representation of flexibility resources for interoperability, (3) integrating occupant impacts into the quantification and optimization of energy flexibility, and (4) developing requirements and credits of energy flexibility in building energy codes and standards. Findings from the review can inform future research and development of energy flexible buildings which are essential to a reliable and resilient power grid.

Li, H↗
DOE OSTI2019

A Highly Efficient Control Framework for Centralized Residential Charging Coordination of Large Electric Vehicle Populations

The potential for widespread adoption of plug-in electric vehicles (PEVs) brings with it the potential for negative impacts on the electric grid from electric vehicle charging. Uncoordinated PEV charging may increase electricity demand during peak hours, which could create concerns for the grid as the number of PEVs increases. Therefore, it is important to coordinate charging to alleviate potential negative impacts. Centralized charging coordination is preferred by grid operator over distributed control strategies because it can systematically allocate energy across a large population of PEVs and achieve global coordination benefits. However, centralized methods presented in the literature to date require prohibitively expensive computational resources and lack realistic PEV charging models. As a result, they cannot achieve the efficiency and accuracy required to implement charging coordination in the real world. This paper introduces a highly efficient receding horizon control framework that enables dynamic charging coordination for large PEV populations. A two-stage hierarchical optimization routine is proposed that aggregates individual PEV charging flexibility to reduce the computational complexity of the optimization process. The control framework is based on high-fidelity, validated charging system models and charging behavior models derived from a real-world data set of residential charging activities collected from thousands of charging stations over multiple years. Case studies illustrate that the proposed charging control framework is capable of effectively coordinating the charging of millions of PEVs using a standard desktop computer.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2017

Empirical Investigations of the Opportunity Limits of Automatic Residential Electric Load Shaping

Residential electric load shaping is often modeled as infrequent, utility-initiated, short-duration deferral of peak demand through direct load control. In contrast, modeled herein is the potential for frequent, transactive, intraday, consumer-configurable load shaping for storage-capable thermostatically controlled electric loads (TCLs), including refrigerators, freezers, and hot water heaters. Unique to this study are 28 months of 15-minute-interval observations of usage in 101 homes in the Pacific Northwest United States that specify exact start, duration, and usage patterns of approximately 25 submetered loads per home. The magnitudes of the load shift from voluntarily-participating TCL appliances are aggregated to form hourly upper and lower load-shaping limits for the coordination of electrical generation, transmission, distribution, storage, and demand. Empirical data are statistically analyzed to define metrics that help quantify load-shaping opportunities.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2019

Machine Learning-Based Investigation of the Associations between Residential Power Consumption and Weather Conditions

Machine learning feature selection analyses were conducted to understand the impact of various weather attributes on power electricity demand and its components in the northwest United States. Load profiles data were obtained from the Northwest Energy Efficiency Alliance (NEEA) and processed to yield hourly load profiles with the same temporal resolution as the weather conditions data obtained from the National Oceanic and Atmospheric Administration (NOAA) for representative weather stations. The data were divided into five seasons; for each season, for each load component, the influences of weather factors were evaluated and quantified using cross-correlation, principal component analysis, and mutual information evaluation; then predictive models were developed based on the ranked/screened factors using the regression tree (RT) approach. After multi-fold cross-validation, the optimal complexity/depth of the regress tree models is found to vary for different load components, and the prediction accuracy using RT and weather data can be higher than 80% for heating and refrigeration, or lower than 30% for vent and cooking. The study provides guidance on improvement of load profile generation, or even serves as a standalone predictive tool for approximating load profiles in balance authorities or climate zones where load profile data is absent.

load composite, load profiling, NEEA, mutual infor↗
DOE OSTI2023

Impact of Control on Availability and Cycling of Residential HVAC in a Real-World Experiment

Demand response is an important emerging part of smart grids and there is a large stream of research from theoretical and modeling perspectives. However, there is relatively little experimental evidence that could help researchers and building operators make informed decisions on best practices for modeling, developing, and deployment of control mechanisms. We contribute to the body of experimental research by providing numerical insights into the role and availability of residential HVAC systems for control. We share the findings on the duration of the cooling cycle, off cycle, and temperature settling time of HVAC systems from data collected from a smart neighborhood located in Atlanta, GA.

cycling↗
DOE OSTI2018

Residential Advanced Photovoltaic Inverter Pilot Study Results for Select Distribution Secondaries in Hawai'i

Penetration levels of residential rooftop solar photovoltaic (PV) generation on the Hawaiian island of O'ahu have increased significantly in recent years, with many circuits now at the limits of their PV hosting capacity. NREL and Hawaiian Electric have used this opportunity to deploy advanced inverters at new customer installations that would not otherwise have been approved, as a pilot study to gain first-hand operational field data and experience on the impact of inverter-based grid support functions. At each customer location, the deployed advanced inverters were remotely controlled and monitored. Additionally, customer AMI (smart meter) and secondary distribution transformer data was also available for the analysis. The analysis focused on quantifying the customer behind-the-meter voltage rise due to PV production, determining the customer voltage rise with advanced inverters in unity power factor as well as advanced grid support function modes, and estimating the curtailment when inverters have Volt-VAR and Volt-Watt enabled. The results show that: 1) Behind-the-meter voltage rise is often not negligible. 2) An inverter's operating point on a Volt-VAR/Volt-Watt curve depends strongly on the design of the secondary system on which it is installed. 3) The mitigation of voltage rise on the secondary system using Volt-VAR may not be effective if only a small proportion of inverters have grid support enabled, or if the reactance/resistance (X/R) ratio of the grid is low. 4) Volt-Watt curtailment can be estimated using co-located irradiance sensors but there may be opportunities to estimate it using inverter internal electrical measurements. 5) Estimated curtailment is very low for the locations analyzed to date.

14 SOLAR ENERGY↗
DOE OSTI2017

Tracking the Sun 10: The Installed Price of Residential and Non-Residential Photovoltaic Systems in the United States

Berkeley Lab’s Tracking the Sun report series is dedicated to summarizing trends in the installed price of grid-connected, residential and non-residential systems solar photovoltaic (PV) systems in the United States. The present report, the tenth edition in the series, focuses on systems installed through year-end 2016, with preliminary data for the first half of 2017. The report provides an overview of both long-term and more-recent trends, highlighting key drivers for installed price declines over different time horizons. The report also extensively characterizes the widespread variability in system pricing, comparing installed prices across states, market segments, installers, and various system and technology characteristics. The trends described in this report derive from project-level data collected by state agencies and utilities that administer PV incentive programs, solar renewable energy credit (SREC) registration systems, or interconnection processes. In total, data for this report were compiled and cleaned for more than 1.1 million individual PV systems, though the analysis in the report is based on a subset of that sample, consisting of roughly 630,000 systems with available installed price data. The full underlying dataset of project-level data (excluding any confidential information) is available in a public data file, for use by other researchers and analysts.

14 SOLAR ENERGY↗
DOE OSTI2018

Assessing the PACE of California residential solar deployment: Impacts of Property Assessed Clean Energy programs on residential solar photovoltaic deployment in California, 2010-2015

A new study by Berkeley Lab found that residential Property Assessed Clean Energy (R-PACE) programs increased deployment of residential solar photovoltaic (PV) systems in California, raising it by about 7-12% in cities that adopt these programs. R-PACE is a financing mechanism that uses a voluntary property tax assessment, paid off over time, to facilitate energy improvements and, in some jurisdictions, water and resilience measures. While previous studies demonstrated that early, regional R-PACE programs increased solar PV deployment, this new analysis is the first to demonstrate these impacts from the large, statewide R-PACE programs dominating the California market today, which use private capital to fund the upfront costs of the improvements. Berkeley Lab estimated the impacts using econometric techniques on two samples: -Large cities only, allowing annual demographic and economic data as control variables -All California cities, without these annual data Analysis of both samples controls for several factors other than R-PACE that would be expected to drive solar PV deployment. We infer that on average, cities with R-PACE programs were associated with greater solar PV deployment in our study period (2010-2015). In the large cities sample, solar PV deployment in jurisdictions with R-PACE programs was higher by 1.1 watts per owner-occupied household per month, or 12%. Across all cities, solar PV deployment in jurisdictions with R-PACE programs was higher by 0.6 watts per owner-occupied household per month, or 7%. The large cities results are statistically significant at conventional levels; the all-cities results are not. The estimates imply that the majority of solar PV deployment financed by R-PACE programs would likely not have occurred in their absence. Results suggest that R-PACE programs have increased PV deployment in California even in relatively recent years, as R-PACE programs have grown in market share and as alternate approaches for financing solar PV have developed. The U.S. Department of Energy’s Building Technologies Office supported this research.

14 SOLAR ENERGY↗
DOE OSTI2020

Calculating Average Hot Water Mixes of Residential Plumbing Fittings Using the ANSI 301-2019 Hot Water Draw Model and National Residential Data to Estimate Hot Water Use in Showerheads and Lavatory Faucets

Available studies of hot water use percentages may not necessarily be generalized to a national level given regional differences, varying methodological approaches, and limited sample sizes. While some publicly available usage data, reports, and surveys estimate actual household usage, a lack of water use data specific to end uses make more precise savings calculations difficult. Additionally, most hot water draw models tend to focus on overall household use and may not readily estimate lavatory fixture use. However, reviewing more recent studies and standards enables the U.S. Environmental Protection Agency’s WaterSense program to update its estimates for hot water use and consumers’ corresponding energy and monetary savings to better reflect realworld conditions. This report specifically focuses on improving hot water use and savings estimates of lavatory faucets and showerheads. To estimate the hot water use of lavatory faucets and showerheads, we employed the 2015 Residential Energy Consumption Surveys (RECS) microdata alongside the ANSI 301-2019 Hot Water Draw Model. These estimates account for regional differences in hot water use, including regional cold water inlet temperatures. As a result, the refinements presented in this report are more robust, more recent, and better describe the geographic variation than previous inputs used by the WaterSense program. In addition, the approach described in this paper can be updated over time or tailored to regionally specific needs given available inputs. We conclude that hot water percentages for showers and faucets calculated using publicly available national data are close to the percentages found by regional studies and are consistent with household-level models of water use.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

ENERGY STAR Residential Water Heater Specification and Test Method for Connected Residential Water Heaters

Electric water heaters have long been used as a tool for demand response due to their inherent thermal storage and large electric load. Traditionally, electric water heaters have been controlled by external load control switches, but that type of control does not work well with more efficient heat pump water heaters and cannot ensure that consumers have adequate hot water. Water heater manufacturers are adding more sophisticated controls that allow utilities or consumers to control their water heaters in new ways that can provide demand response without impacting consumer comfort. Further, the electric utility grid has seen a rapid increase the availability of renewable energy, which, depending on the type of renewable energy, can provide large amounts of energy for a portion of the day, but reduced or no energy at other times. In response to these advances in controls, availability of periodic renewable energy, and in an effort to have a standard which can be applied at a national level, ENERGY STAR and the Department of Energy have developed a Product Specification and Test Method for Connected Residential Water Heaters. In this session, we will discuss the new specification and test method, as well as show some initial results from running the new test method with two different HPWHs at NREL.

connected water heater↗