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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Recent Improvements in PV+Battery Modeling in NREL's System Advisor Model

This poster covers recent updates to the NREL System Advisor Model's battery model that can be coupled to the PV model to add value to both front of meter and behind the meter systems. Topics include new dispatch algorithms focusing on smoothing the output of a PV plant to meet ramp rate requirements and responding to price signals to maximize system revenue, validated battery lifetime models, grid outage simulations and resiliency metrics, and the new levelized cost of storage (LCOS) metric. We will also share preliminary results from NREL analysis projects using these features.

battery↗
DOE OSTI2023

GETEM in the System Advisor Model (SAM)

This presentation on GETEM in the System Advisor Model (SAM) was part of a webinar to internal and external geothermal on January 19th, 2023. The presentation includes an overview of SAM and discussion of the GETEM model implementation in SAM.

geothermal↗
DOE OSTI2023

System Advisor Model (SAM) and PVWatts

The System Advisor Model (SAM) is a free techno-economic software model that facilitates decision-making for people in the renewable energy industry. PVWatts estimates the energy production of grid-connected photovoltaic energy systems throughout the world. It allows homeowners, small building owners, installers, and manufacturers to easily develop estimates of the performance of potential photovoltaic installations.

energy planning↗
DOE OSTI2023

Recent and Planned Improvements to the System Advisor Model (SAM)

This talk will focus on recent and planned modeling improvements to the NREL System Advisor ModelTM (SAM), including PV hourly clipping correction, expanded geographic scope of PVWatts including Ukraine, additional options for hybrids, and enhanced PySAM and GUI interoperability. Additional topics will also include: bifacial modeling features including irradiance on the ground for agrivoltaics, PV uncertainty simulation features, and integrations with other NREL and industry tools.

battery↗
DOE OSTI2024

Recent and Planned Improvements to the System Advisor Model (SAM)

This talk will focus on recent and planned modeling improvements to the NREL System Advisor ModelTM (SAM), with recently released features including PV hourly clipping correction, expanded geographic scope of SAM's NSRDB interface to Europe and Africa, and additional options for hybrids. Upcoming improvements include a case comparison feature, improved visualizations, and extensions of PVWatts for battery modeling and utility rate calculations.

batteries↗
DOE OSTI2018

DC-Connected Solar Plus Storage Modeling and Analysis for Behind-the-Meter Systems in the System Advisor Model

A detailed model for PV plus DC-connected batteries was developed. This model was compared to an existing ACconnected battery model in the System Advisor Model (SAM) tool using a hypothetical Honolulu residence with a PV plus storage system. The stand-alone PV system was shown to provide the most value; however due to the increased difficulty of PV systems being approved for grid interconnection in Hawaii, it is valuable to install an AC or DC connected battery to enable full PV self-consumption under a less restrictive interconnection option. In that case both battery systems enabled full PV selfconsumption at the residence, requiring no power to be exported to the grid. The DC-connected battery system captured energy from the PV array which would have also been clipped due to inverter limitations. For a PV system with DC/AC ratio of 1.23, the battery configurations produced net-present values within 1% of each other, but when the DC/AC ratio increased to 1.85, the DC-connected system increased the net-present value by 13%.

14 SOLAR ENERGY↗
DOE OSTI2018

Joint Evaluation of System Host and Developer Financial Perspectives within the System Advisor Model

The System Advisor Model (SAM)11https://sam.nrel.gov already contains several RE project financing including residential mortgage, commercial loan partnership flips, and third-party ownership. However, a variety of SAM users wanted to evaluate a system in which a third party owned the system, both from the developer's perspective and the system host perspective concurrently. Therefore, a new host and developer co-model has been added and is described. This model effectively combines the previously-released 'third party ownership' and 'Single owner' models into the same analysis.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2019

PySAM (Python Wrapper for System Advisor Model "SAM") [SWR-19-57]

PySAM is a Python wrapper for the National Renewable Energy Laboratory’s System Advisor Model (SAM). SAM is a performance and financial model designed to facilitate decision making for people involved in the renewable energy industry. PySAM provides a native Python interface for the models found in SAM Simulation Core, SSC.

Gilman, Paul↗
DOE OSTI2017

Validation of PV-RPM Code in the System Advisor Model.

This paper describes efforts made by Sandia National Laboratories (SNL) and the National Renewable Energy Laboratory (NREL) to validate the SNL developed PV Reliability Performance Model (PV - RPM) algorithm as implemented in the NREL System Advisor Model (SAM). The PV - RPM model is a library of functions that estimates component failure and repair in a photovoltaic system over a desired simulation period. The failure and repair distributions in this paper are probabilistic representations of component failure and repair based on data collected by SNL for a PV power plant operating in Arizona. The validation effort focuses on whether the failure and repair dist ributions used in the SAM implementation result in estimated failures that match the expected failures developed in the proof - of - concept implementation. Results indicate that the SAM implementation of PV - RPM provides the same results as the proof - of - concep t implementation, indicating the algorithms were reproduced successfully.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Informing Mexico's Distributed Generation Policy with System Advisor Model (SAM) Analysis

The Government of Mexico recognizes the potential for clean distributed generation (DG) to meaningfully contribute to Mexico's clean energy and emissions reduction goals. However, important questions remain about how to fairly value DG and foster inclusive and equitable market growth that is beneficial to investors, electricity ratepayers, electricity distributors, and society. The U.S. National Renewable Energy Laboratory (NREL) has partnered with power sector institutions and stakeholders in Mexico to provide timely analytical support and expertise to help inform policymaking processes on clean DG. This document describes two technical assistance interventions that used the System Advisor Model (SAM) to inform Mexico's DG policymaking processes with a focus on rooftop solar regulation and policy.

14 SOLAR ENERGY↗
DOE OSTI2026

Performance and Reliability Assessment of the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) Data Advisor (ADA)

The Atmospheric Radiation Measurement (ARM) User Facility provides one of the world's largest openly accessible repositories of atmospheric observations through the ARM Data Discovery platform. Although the repository contains more than three decades of measurements collected from permanent observatories, mobile facilities, aircraft campaigns, and field experiments, identifying appropriate datasets can be challenging, particularly for new users unfamiliar with ARM instrumentation and datastream organization. To improve data accessibility, the ARM Data Center developed the ARM Data Advisor (ADA), an artificial intelligence-powered assistant designed to facilitate scientific data discovery, dataset interpretation, and user guidance. This report evaluates ADA's performance as a domain-specific scientific assistant using realistic atmospheric science workflows. The evaluation examines five key capabilities: data retrieval and curation efficiency, hallucination resistance, scientific reasoning, response to ambiguous queries, and content retention and session continuity. Representative prompts were developed to simulate typical interactions between researchers and the ARM Data Discovery platform, and ADA's responses were assessed for retrieval completeness, scientific accuracy, consistency, and practical usefulness. In these representative tests, ADA reduced the complexity of discovering and accessing ARM datasets by recommending appropriate datastreams, explaining instrumentation, interpreting metadata, and assisting with data processing workflows. ADA also exhibits strong domain knowledge of atmospheric science terminology and generally resists hallucination by acknowledging unavailable datasets and requesting clarification when appropriate. Overall, the results indicate that ADA represents a promising advancement in scientific data discovery within the ARM User Facility and has considerable potential to improve researcher productivity, particularly for new users and interdisciplinary scientists seeking efficient access to ARM observations.

Salvador, Christian [ORNL] (ORCID:0000000283287777↗
DOE OSTI2025

Updating the Building Science Advisor (BSA): A Tool to Assist in the Design of Durable Building Envelopes

Predicting the moisture durability of building envelope components remains challenging due to multiple influencing factors, including material selection, assembly positioning, local climate conditions, air tightness, interior environment, and construction quality. Building codes increasingly emphasize energy efficiency through enhanced insulation and tighter envelopes but offer limited guidance on moisture durability considerations. Consequently, builders face uncertainty, particularly as new materials and assemblies enter the market.The Building Science Advisor (BSA) is a free, web-based expert system developed to address these challenges by providing actionable insights into the moisture durability and energy efficiency of both new and retrofit wall designs. Recently updated, we are now providing version 3.0 of the tool. BSA features significant user interface improvements, enhancing navigation and user interaction through a refreshed, intuitive design. Additionally, the tool incorporates a newly developed database containing pre-simulated wall assembly cases, significantly reducing response times and improving the accuracy of moisture durability assessments. Furthermore, the updated BSA includes moisture content as a performance criterion, providing users with a more comprehensive understanding of moisture-related durability risks. These enhancements enable rapid, reliable assessments tailored to specific climate zones and local building practices. BSA continues to offer targeted guidance on wall retrofit scenarios and delivers access to an expanded library of location-specific building science resources.This paper describes these key updates, highlighting the enhanced features, expanded capabilities, and overall improvements to user experience and educational content. The paper includes a demonstration that illustrates how the revised BSA effectively supports practitioners in designing durable, energy-efficient building envelope assemblies.

Salonvaara, Mikael [ORNL] (ORCID:0000000318991554)↗
NASA NTRS1987

The load shedding advisor: An example of a crisis-response expert system

A Prolog-based prototype expert system is described that was implemented by the Network Operations Branch of the NASA Goddard Space Flight Center. The purpose of the prototype was to test whether a small, inexpensive computer system could be used to host a load shedding advisor, a system which would monitor major physical environment parameters in a computer facility, then recommend appropriate operator reponses whenever a serious condition was detected. The resulting prototype performed significantly to efficiency gains achieved by replacing a purely rule-based design methodology with a hybrid approach that combined procedural, entity-relationship, and rule-based methods.

Bollinger, Terry B.↗
NASA NTRS1989

An intelligent advisor for the design manager

A design problem is viewed as a complex system divisible into modules. Before the design of a complex system can begin, much time and money are spent in determining the couplings among modules and the presence of iterative loops. This is important because the design manager must know how to group the modules into substems and how to assign subsystems to design teams so that changes in one subsystem will have predictable effects on other subsystems. Determining these subsystems is not an easy, straightforward process and often important couplings are overlooked. Moreover, the planning task must be repeated as new information becomes available or as the design specifications change. The purchase of this research effort is to develop a knowledge-based tool to act as an intelligent advisor for the design manager. This tool identifies the subsystems of a complex design problem, orders them into a well-structured format, and marks the couplings among the subsystems to facilitate the use of multilevel tools. The tool was tested in the decomposition of the COFS (Control of Flexible Structures) mast design which has about 50 modules. This test indicated that this type of approach could lead to a substantial savings by organizing and displaying a complex problem as a sequence of subsystems easily divisible among design teams.

Rogers, James L.↗
NASA NTRS1989

Controller evaluations of the descent advisor automation aid

An automation aid to assist air traffic controllers in efficiently spacing traffic and meeting arrival times at a fix has been developed at NASA Ames Research Center. The automation aid, referred to as the descent advisor (DA), is based on accurate models of aircraft performance and weather conditions. The DA generates suggested clearances, including both top-of-descent point and speed profile data, for one or more aircraft in order to achieve specific time or distance separation objectives. The DA algorithm is interfaced with a mouse-based, menu-driven controller display that allows the air traffic controller to interactively use its accurate predictive capability to resolve conflicts and issue advisories to arrival aircraft. This paper focuses on operational issues concerning the utilization of the DA, specifically, how the DA can be used for prediction, intrail spacing, and metering. In order to evaluate the DA, a real time simulation was conducted using both current and retired controller subjects. Controllers operated in teams of two, as they do in the present environment; issues of training and team interaction will be discussed. Evaluations by controllers indicated considerable enthusiasm for the DA aid, and provided specific recommendations for using the tool effectively.

Tobias, Leonard↗
NASA NTRS1989

Controller evaluations of the descent advisor automation aid

An automation aid to assist air traffic controllers in efficiently spacing traffic and meeting arrival times at a fix has been developed at NASA Ames Research Center. The automation aid, referred to as the descent advisor (DA), is based on accurate models of aircraft performance and weather conditions. The DA generates suggested clearances, including both top-of-descent point and speed profile data, for one or more aircraft in order to achieve specific time or distance separation objectives. The DA algorithm is interfaced with a mouse-based, menu-driven controller display that allows the air traffic controller to interactively use its accurate predictive capability to resolve conflicts and issue advisories to arrival aircraft. This paper focuses on operational issues concerning the utilization of the DA, specifically, how the DA can be used for prediction, intrail spacing, and metering. In order to evaluate the DA, a real time simulation was conducted using both current and retired controller subjects. Controllers operated in teams of two, as they do in the present environment; issues of training and team interaction will be discussed. Evaluations by controllers indicated considerable enthusiasm for the DA aid, and provided specific recommendations for using the tool effectively.

Tobias, Leonard↗
NASA NTRS1991

Simulation Test Of Descent Advisor

Report describes piloted-simulation test of Descent Advisor (DA), subsystem of larger automation system being developed to assist human air-traffic controllers and pilots. Focuses on results of piloted simulation, in which airline crews executed controller-issued descent advisories along standard curved-path arrival routes. Crews able to achieve arrival-time precision of plus or minus 20 seconds at metering fix. Analysis of errors generated in turns resulted in further enhancements of algorithm to increase accuracies of its predicted trajectories. Evaluations by pilots indicate general support for DA concept and provide specific recommendations for improvement.

Davis, Thomas J.↗