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SAM Software Quality Assurance Plan Implementation and NQA-1 Assessment

The System Analysis Module (SAM) is an advanced and modern system analysis tool being developed at Argonne National Laboratory under the U.S. DOE Office of Nuclear Energy’s Nuclear Energy Advanced Modeling and Simulation (NEAMS) program. As a modern-day software, SAM development included efforts to follow best practices in software development. These best practices include version control using git, independent reviews of development activities, and detailed descriptions of developments and bug fixes using the GitLab issue and merge request system. In Fiscal Year 2023 (FY23), the SAM development team set out to formalize a Software Quality Assurance (SQA) program that allowed industry partners to credit the informal steps being taken by the SAM development team to ensure the quality of the software. As part of formalizing an SQA program, a SQA Plan (SQAP) was developed, implemented, and assessed. The SAM SQAP targets compliance with NQA-1-2008/2009 Addenda. The SQAP builds on the MOOSE SQAP and the Argonne SSQAPP while accounting for the needs of the multi-organization SAM development team. Modifications to the SAM repository structure, including a new testing system, updated test cases, and the development of an internal website, facilitate the implementation of the SAM SQAP. The initial assessment of the SAM SQAP indicated that the SAM SQAP was adequately and effectively implemented and additional work was required to improve the compliance of the SAM SQAP with NQA-1 2008/2009 Addenda. Several improvements to the SQAP have already been drafted to address these assessments and future work is planned to further improve the SAM SQAP in support of end-user needs.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Hybrid Solar Thermal Energy System for District Heating Application

Solar district heating (SDH) systems can be good alternatives to conventional systems when they are optimized with hybrid configurations and thermal energy storage (TES). In this scope, a hybrid renewable thermal energy system (RTES) model has been built combining flat plate collector (FPC) solar system with parabolic trough collector (PTC) system via a heat exchanger and coupled with TES. To undertake the hybridization of the system, System Advisor Model (SAM) software was modified, which allowed control over configurations and more accurate modelling of heat transfer between the collectors. The model is first compared to an existing hybrid solar district heating systems (DHS) system in Taars, Denmark. The results showed a good correlation with an overestimation of only 6.4% compared to most recent heat output. Then the same system configuration was modeled in different geographic locations to investigate the impact of changes in direct normal irradiance (DNI) to the heat sink thermal output of the hybrid system. The results showed that the annual net thermal power output in California, USA can be three times more than the annual net thermal power output in Taars, Denmark. Finally, multiple hybrid configurations with varying solar field sizes were simulated based on the heat demand of two different university campuses DHS. The results showed that, retrofit applications of this hybrid DHS system coupled with TES could reduce the natural gas consumption of the existing systems between 25% and 41%. The use of hybrid RTES highlighted in this paper can be extended to many more opportunities.

district heating↗

SAM Photovoltaic Model Technical Reference 2016 Update

This manual describes the photovoltaic performance model in the System Advisor Model (SAM) software, Version 2016.3.14 Revision 4 (SSC Version 160). It is an update to the 2015 edition of the manual, which describes the photovoltaic model in SAM 2015.1.30 (SSC 41). This new edition includes corrections of errors in the 2015 edition and descriptions of new features introduced in SAM 2016.3.14, including: 3D shade calculator Battery storage model DC power optimizer loss inputs Snow loss model Plane-of-array irradiance input from weather file option Support for sub-hourly simulations Self-shading works with all four subarrays, and uses same algorithm for fixed arrays and one-axis tracking Linear self-shading algorithm for thin-film modules Loss percentages replace derate factors. The photovoltaic performance model is one of the modules in the SAM Simulation Core (SSC), which is part of both SAM and the SAM SDK. SAM is a user-friedly desktop application for analysis of renewable energy projects. The SAM SDK (Software Development Kit) is for developers writing their own renewable energy analysis software based on SSC. This manual is written for users of both SAM and the SAM SDK wanting to learn more about the details of SAM's photovoltaic model.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Software for Alignment of Segments of a Telescope Mirror

The Segment Alignment Maintenance System (SAMS) software is designed to maintain the overall focus and figure of the large segmented primary mirror of the Hobby-Eberly Telescope. This software reads measurements made by sensors attached to the segments of the primary mirror and from these measurements computes optimal control values to send to actuators that move the mirror segments.

Hall, Drew P.↗

CSP-Plant Modeling Guidelines and Compliance of the System Advisor Model (SAM)

Accurately modeling risks, costs, and electricity output is essential to the financing and advancement of concentrating solar power projects. To address this need, a group of CSP experts created a guideline document, titled SolarPACES Guideline for Bankable STE Yield Assessment [1]. To make this information more accessible and allow stakeholders to test specific models against the recommendations, the guidelines have been condensed into a spreadsheet-based checklist. The checklist was applied to NREL's System Advisor Model (SAM) software, providing useful feedback to both the checklist group and the SAM development team. This study showed strong agreement between SAM and the guidelines, demonstrated the use of the guidelines in model validation, and resulted in several recommended improvements to SAM.

14 SOLAR ENERGY↗

LK Scripting Language [SWR-16-07]

The LK scripting language is a simple and fast computer programming language designed for easy integration with existing software to enable automation of tasks. The LK language is used by NREL’s System Advisor Model (SAM), the SAM Software Development Kit (SDK), and SolTrace products. LK is easy extensible and adaptable to new software due to its small footprint and is designed to be statically linked into other software. It is written in standard C++, is cross-platform (Windows, Linux, and OSX), and includes optional portions that enable direct integration with graphical user interfaces written in the open source C++ wxWidgets Version 3.0+ toolkit.

Source record↗

LK Scripting Language

The LK scripting language is a simple and fast computer programming language designed for easy integration with existing software to enable automation of tasks. The LK language is used by NREL’s System Advisor Model (SAM), the SAM Software Development Kit (SDK), and SolTrace products. LK is easy extensible and adaptable to new software due to its small footprint and is designed to be statically linked into other software. It is written in standard C++, is cross-platform (Windows, Linux, and OSX), and includes optional portions that enable direct integration with graphical user interfaces written in the open source C++ wxWidgets Version 3.0+ toolkit.

Source record↗

ISS Solar Array Management

The International Space Station (ISS) Solar Array Management (SAM) software toolset provides the capabilities necessary to operate a spacecraft with complex solar array constraints. It monitors spacecraft telemetry and provides interpretations of solar array constraint data in an intuitive manner. The toolset provides extensive situational awareness to ensure mission success by analyzing power generation needs, array motion constraints, and structural loading situations. The software suite consists of several components including samCS (constraint set selector), samShadyTimers (array shadowing timers), samWin (visualization GUI), samLock (array motion constraint computation), and samJet (attitude control system configuration selector). It provides high availability and uptime for extended and continuous mission support. It is able to support two-degrees-of-freedom (DOF) array positioning and supports up to ten simultaneous constraints with intuitive 1D and 2D decision support visualizations of constraint data. Display synchronization is enabled across a networked control center and multiple methods for constraint data interpolation are supported. Use of this software toolset increases flight safety, reduces mission support effort, optimizes solar array operation for achieving mission goals, and has run for weeks at a time without issues. The SAM toolset is currently used in ISS real-time mission operations.

Williams, James P.↗

Stand-Alone and Hybrid Electric Thermal Energy Storage in the System Advisor Model

This project developed stand-alone electric-thermal energy storage (ETES), stand-alone pumped thermal energy storage (PTES), and hybrid molten-salt power tower (MSPT)-ETES performance and dispatch optimization techno-economic models. The models are available to the public through the System Advisor Model (SAM) software, scripting, and as open-source code. We compared results of the dispatch model to PLEXOS dispatch of a similar generator using the same initial grid pricing signal and found our dispatch model performed well, but closer agreement between the models was limited by the inherent differences between price-taker and unit commitment models. Nevertheless, the price-taker models developed in this project are useful to analyze proposed ETES and PTES technologies because they provide more detailed system and component models, solve several orders of magnitude faster, and are available as free open-source software. The model results represent the most optimistic returns considering grid arbitrage from the input electricity pricing, so the financial results can be applied as a feasibility stage-gate. We also submitted a journal draft paper that describes the ETES dispatch model methodology and demonstrates model functionality. An accepted journal article will serve as peer-reviewed documentation for the models, along with the open-source code, SAM help-menu content, and eventually this final project report.

14 SOLAR ENERGY↗

Incorporation of NREL Solar Advisor Model Photovoltaic Capabilities with GridLAB-D

This report provides a summary of the work updating the photovoltaic model inside GridLAB-D. The National Renewable Energy Laboratory Solar Advisor Model (SAM) was utilized as a basis for algorithms and validation of the new implementation. Subsequent testing revealed that the two implementations are nearly identical in both solar impacts and power output levels. This synergized model aides the system-level impact studies of GridLAB-D, but also allows more specific details of a particular site to be explored via the SAM software.

GridLAB-D↗

System Advisor Model, SAM 2014.1.14: General Description

This document describes the capabilities of the U.S. Department of Energy and National Renewable Energy Laboratory's System Advisor Model (SAM), Version 2013.9.20, released on September 9, 2013. SAM is a computer model that calculates performance and financial metrics of renewable energy systems. Project developers, policy makers, equipment manufacturers, and researchers use graphs and tables of SAM results in the process of evaluating financial, technology, and incentive options for renewable energy projects. SAM simulates the performance of photovoltaic, concentrating solar power, solar water heating, wind, geothermal, biomass, and conventional power systems. The financial model can represent financial structures for projects that either buy and sell electricity at retail rates (residential and commercial) or sell electricity at a price determined in a power purchase agreement (utility). SAM's advanced simulation options facilitate parametric and sensitivity analyses, and statistical analysis capabilities are available for Monte Carlo simulation and weather variability (P50/P90) studies. SAM can also read input variables from Microsoft Excel worksheets. For software developers, the SAM software development kit (SDK) makes it possible to use SAM simulation modules in their applications written in C/C++, C#, Java, Python, and MATLAB. NREL provides both SAM and the SDK as free downloads at http://sam.nrel.gov. Technical support and more information about the software are available on the website.

14 SOLAR ENERGY↗

System Advisor Model (SAM) General Description (Version 2017.9.5)

This document describes the capabilities of the System Advisor Model (SAM) developed and distributed by the U.S. Department of Energy's National Renewable Energy Laboratory. The document is for potential users and others wanting to learn about the model's capabilities. SAM is a techno-economic computer model that calculates performance and financial metrics of renewable energy projects. Project developers, policy makers, equipment manufacturers, and researchers use graphs and tables of SAM results in the process of evaluating financial, technology, and incentive options for renewable energy projects. SAM simulates the performance of photovoltaic, concentrating solar power, solar water heating, wind, geothermal, biomass, and conventional power systems. The financial models are for projects that either buy and sell electricity at retail rates (residential and commercial) or sell electricity at a price determined in a power purchase agreement (PPA). SAM's simulation tools facilitate parametric and sensitivity analyses, Monte Carlo simulation and weather variability (P50/P90) studies. SAM can also read input variables from Microsoft Excel worksheets. For software developers, the SAM software development kit (SDK) makes it possible to use SAM simulation modules in their applications written in C/C plus plus, C sharp, Java, Python, MATLAB, and other languages. NREL provides both SAM and the SDK as free downloads at https://sam.nrel.gov. SAM is an open source project, so its source code is available to the public. Researchers can study the code to understand the model algorithms, and software programmers can contribute their own models and enhancements to the project. Technical support and more information about the software are available on the website.

47 OTHER INSTRUMENTATION↗

System Advisor Model, SAM 2011.12.2: General Description

This document describes the capabilities of the U.S. Department of Energy and National Renewable Energy Laboratory's System Advisor Model (SAM), Version 2011.12.2, released on December 2, 2011. SAM is software that models the cost and performance of renewable energy systems. Project developers, policy makers, equipment manufacturers, and researchers use graphs and tables of SAM results in the process of evaluating financial, technology, and incentive options for renewable energy projects. SAM simulates the performance of solar, wind, geothermal, biomass, and conventional power systems. The financial model can represent financing structures for projects that either buy and sell electricity at retail rates (residential and commercial) or sell electricity at a price determined in a power purchase agreement (utility). Advanced analysis options facilitate parametric, sensitivity, and statistical analyses, and allow for interfacing SAM with Microsoft Excel or with other computer programs. SAM is available as a free download at http://sam.nrel.gov. Technical support and more information about the software are available on the website.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Batteries in SAM 2020.2.29: Behind-the-Meter Systems

Provide an overview of behind the meter dispatch methods in the SAM 2020.2.29 software for analysis of residential, commercial, and generic battery systems. Discuss the details of SAM's automatic peak shaving and manual energy arbitrage dispatch options.

41 EE - Solar Energy Technologies Office (EE-4S)↗

Dispatch optimization of electric thermal energy storage within System Advisor Model

A stand-alone electric thermal energy storage (ETES) system converts low-value electricity into heat using resistance heating elements. During periods of high-value electricity, an ETES system uses a thermodynamic power cycle to convert stored thermal energy back to electricity. These dispatchable systems derive value from their ability to store energy when prices are low and generate electricity when prices are favorable, i.e., energy arbitrage. Consequently, dispatch optimization of system operations, through maximizing revenue subject to system constraints, is essential to evaluate the economic value of a particular system design. While stand-alone ETES systems offer potential advantages as dispatchable grid storage technologies, there is a lack of a neutral third-party, publicly available, open-source model to evaluate the performance, dispatch, and financial viability of these systems. To address this problem, we have developed a techno-economic model for stand-alone ETES systems, within National Renewable Energy Laboratory's (NREL's) System Advisor Model (SAM). We implement a mixed-integer linear program to determine an ETES optimal operating schedule that maximizes electricity sales less maintenance costs caused by operation and cycling given temporal-varying grid electricity prices. Our contributions include a mixed-integer linear program for energy arbitrage of an ETES system, an ETES performance model through a publicly-available software (i.e., SAM), and an exercise of our model through case studies that compare ETES operational strategies and annual financial metrics. With our dispatch optimization model, we were able to improve revenue by 20% compared to a myopic heuristic while reducing the operational cost of the ETES system through decreases in cycle starts, cycles per day, and heater starts.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Improvements to PVWatts for Fixed and One-Axis Tracking Systems

This work presents improvements to the widely used NREL PVWatts photovoltaic system energy model to improve modeling accuracy for typical fixed and one axis system designs. The aim is to calculate losses in the PV system assuming typical modern system design practices, while maintaining simplicity by keeping the required set of input parameters small. These improvements allow users to more credibly and quickly evaluate competing system designs in early stage feasibility. Common submodels for module cover, spectral, snow, tracker, transformer, plant controller, and self-shading losses, in addition to a bifacial gain option, are incorporated into the PVWatts model, and are shown to improve PVWatts' system performance prediction capabilities without major impact to ease of use. We anticipate including these improvements in a future release of NREL's open source PVWatts code, and some of the features may become available in the System Advisor Model (SAM) desktop software as well as the popular PVWatts web application.

14 SOLAR ENERGY↗

Specification of parameters for development of a spatial database for drought monitoring and famine early warning in the African Sahel

Parameters were described for spatial database to facilitate drought monitoring and famine early warning in the African Sahel. The proposed system, referred to as the African Drought and Famine Information System (ADFIS) is ultimately recommended for implementation with the NASA/FEMA Spatial Analysis and Modeling System (SAMS), a GIS/Dymanic Modeling software package, currently under development. SAMS is derived from FEMA'S Integration Emergency Management Information System (IEMIS) and the Pacific Northwest Laborotory's/Engineering Topographic Laboratory's Airland Battlefield Environment (ALBE) GIS. SAMS is primarily intended for disaster planning and resource management applications with the developing countries. Sources of data for the system would include the Developing Economics Branch of the U.S. Dept. of Agriculture, the World Bank, Tulane University School of Public Health and Tropical Medicine's Famine Early Warning Systems (FEWS) Project, the USAID's Foreign Disaster Assistance Section, the World Resources Institute, the World Meterological Institute, the USGS, the UNFAO, UNICEF, and the United Nations Disaster Relief Organization (UNDRO). Satellite imagery would include decadal AVHRR imagery and Normalized Difference Vegetation Index (NDVI) values from 1981 to the present for the African continent and selected Landsat scenes for the Sudan pilot study. The system is initially conceived for the MicroVAX 2/GPX, running VMS. To facilitate comparative analysis, a global time-series database (1950 to 1987) is included for a basic set of 125 socio-economic variables per country per year. A more detailed database for the Sahelian countries includes soil type, water resources, agricultural production, agricultural import and export, food aid, and consumption. A pilot dataset for the Sudan with over 2,500 variables from the World Bank's ANDREX system, also includes epidemiological data on incidence of kwashiorkor, marasmus, other nutritional deficiencies, and synergistically-related infectious diseases.

Rochon, Gilbert L.↗

CSP-Plant Modeling Guidelines and Compliance of the System Advisor Model (SAM): Preprint

Accurately modeling risks, costs, and electricity output is essential to the financing and advancement of concentrating solar power projects. To address this need, a group of CSP experts created a guideline document, titled SolarPACES Guideline for Bankable STE Yield Assessment (1). To make this information more accessible and allow stakeholders to test specific models against the recommendations, the guidelines have been condensed into a spreadsheet-based checklist. The checklist was applied to NREL's System Advisory Model (SAM) CSP modeling software, providing useful feedback to both the checklist group and the SAM development team. This study showed a strong agreement between SAM and the guidelines, demonstrated the use of the guidelines in model validation, and resulted in several recommended improvements to SAM.

14 SOLAR ENERGY↗