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Results for “System Advisor Model (SAM)”

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 73 records · Page 4
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DOE OSTI2018

Economic Dispatch for DC-Connected Battery Systems on Large PV Plants

Falling costs of energy storage combined with an increasing need to mitigate variable generation integration issues is leading to more PV projects that include batteries. Large PV plants that include batteries face challenges optimizing the value of the power they produce, especially when the batteries are DC-coupled and otherwise clipped power (due to high DC/AC ratio) is available. Multiple charging times and sources must be considered, including: grid charging, charging from PV that would otherwise be exported to the grid, and charging from clipped PV power. Then discharge schedules must be optimized against time-of-day pricing. The National Renewable Energy Laboratory in partnership with Southern Company has developed a heuristic algorithm in the System Advisor Model (SAM) which strategically charges the battery from PV and discharges the battery depending on the time-of-day prices of the PPA, the forecast PV production, and the estimated wear cost of the battery. The algorithm and case study results from a generic plant will be presented with recommendations for future work.

25 ENERGY STORAGE↗
DOE OSTI2012

P50/P90 Analysis for Solar Energy Systems Using the System Advisor Model: Preprint

To secure competitive financing for a solar energy generation project, the economic risk associated with interannual solar resource variability must be quantified. One way to quantify this risk is to calculate exceedance probabilities representing the amount of energy expected to be produced by a plant. Many years of solar radiation and metereological data are required to determine these values,often called P50 or P90 values for the level of certainty they represent. This paper describes the two methods implemented in the National Renewable Energy Laboratory's System Advisor Model (SAM) to calculate P50 and P90 exceedance probabilities for solar energy projects. The methodology and supporting data sets are applicable to photovoltaic, solar water heating, and concentrating solar power(CSP) systems.

14 SOLAR ENERGY↗
DOE OSTI2021

Simulation of PV Variability as a Function of PV Generation and Plant Size: Preprint

The deployment of photovoltaic (PV) systems continues to show significant expansion; however, this growth has brought added attention to issues around the variability of the solar resource. Both spatial and temporal variability exist. Temporal scales can range from the sub-second to multiyear, whereas spatial scales can range from a few meters to tens of kilometers. There are multiple methods described in the literature to quantify PV variability at various spatial and temporal scales. This study focuses on short-term temporal variability and uses similar approaches with the addition of PV plant size a parameter to quantify variability. The method employed here incorporates the normalization of clear- and cloudy-sky conditions and PV plant size to quantify nominal variability metrics. The distribution and fluctuations of these metrics provide relevant information that is useful for system operations. The National Solar Radiation Database (NSRDB) is used to simulate PV variability as a function of PV generation and plant size. Hypothetical but realistic system information at 33 locations is used to model PV generation by feeding NSRDB solar irradiance data to the National Renewable Energy Laboratory’s System Advisor Model (SAM). Over the selected region, it is found that the aggregated ramp rates for the 1-minute data are associated with standard deviations ranging from 0.002–0.055 on a daily basis; however, hourly intervals induce higher aggregated ramp rates than the other timescales. Even though minute-to-minute variations are significant for the 1-minute timescale, the standard deviation aggregated into a daily metric is smaller because of the cancellation of values.

41 EE - Solar Energy Technologies Office (EE-4S)↗
DOE OSTI2021

Understanding Solar Photovoltaic System Performance: An Assessment of 75 Federal Photovoltaic Systems

This report presents a performance analysis of 75 photovoltaic systems based on PV system production data collected as part of a FEMP Federal PV Performance Assessment project combined with co-incident insolation, and ambient temperature to analyze how actual performance compares with a performance model. FEMP collaborated with 17 Federal agencies and sub-agencies to collect the information required to analyze the performance of each system. The systems represent a total capacity of 30,714 kW and range in size from 1 kW to 4,043 kW, with an average size of 410 kW, and were installed between 2011 and 2020. The data is analyzed for Key Performance Indicators, Availability, Performance Ratio and Energy Ratio by comparing the measured production data to model production data. The System Advisor Model (SAM) combines a description of the system (such as inverter capacity, de-rating for temperature, balance-of-system efficiency) with environmental parameters (coincident solar and temperature data) to calculate predicted performance. The performance metrics are calculated by lining up the measured production data with the model estimate on an hour-by-hour, day-by-day, or month-by-month basis (depending on the interval resolution of the production data). A report with system description, photo of the system, special assumptions made for the site, graph of measured production and model production, table of key performance indicators, and links to O&M resources that might improve performance was produced and delivered to site and agency staff with a short on-line briefing.

14 SOLAR ENERGY↗
DOE OSTI2025

Modeling and Analysis of Clean Energy and Storage Technologies (CRADA Final Report, Project 1)

The goal of this project is to provide Southern Company Services, Inc. ("Participant") with custom scripts that can be used to create an average PV energy production profile, calculate lifetime energy value, calculate capacity value, and calculate the resultant financial metrics considering those value streams. Secondly, a fuel-cell model will be added to the public version of System Advisor Model (SAM). This standalone technology will incorporate PV and battery storage, allowing the participant to model the interaction of these three technologies. By adding this capability to a public version of SAM, a broad audience will be able to consider the system performance and financial benefits of installing a fuel cell as a baseline generator with PV. Thirdly, automated dispatch algorithms will be developed and added to SAM. These algorithms will enable Southern Company to dispatch a DC-connected front-of-the-meter battery system while considering price signals and PV clipping behavior. By adding these capabilities to a public version of SAM, users will be able to consider more complex and realistic ways of dispatching a battery system.

14 SOLAR ENERGY↗
DOE OSTI2021

Heuristic Dispatch Based on Price Signals for Behind-the-Meter PV-Battery Systems in the System Advisor Model

The economic potential of a behind-the-meter (BTM) PV-battery system depends greatly on how the battery is dispatched. Different utility rates, system sizes, generation and load profiles can all require different dispatch strategies. This paper presents price signals dispatch, a new algorithm for automated economic dispatch of BTM PV-battery systems, which utilizes 24-hour PV and load forecasts, degradation data, and utility rates. The algorithm is integrated with the System Advisor Model (SAM) tool and is tested with a nonlinear generic electrochemical battery model. Price signals dispatch outperforms SAM’s existing algorithms in cases requiring a balance between demand charge management and energy arbitrage, and in cases where battery degradation imposes a significant cost.

41 EE - Solar Energy Technologies Office (EE-4S)↗
DOE OSTI2021

Heuristic Dispatch Based on Price Signals for Behind-the-Meter PV-Battery Systems in the System Advisor Model: Preprint

The economic potential of a behind-the-meter (BTM) PV-battery system depends greatly on how the battery is dispatched. Different utility rates, system sizes, generation and load profiles can all require different dispatch strategies. This paper presents price signals dispatch, a new algorithm for automated economic dispatch of BTM PV-battery systems, which utilizes 24-hour PV and load forecasts, degradation data, and utility rates. The algorithm is integrated with the System Advisor Model (SAM) tool and is tested with a nonlinear generic electrochemical battery model. Price signals dispatch outperforms SAM’s existing algorithms in cases requiring a balance between demand charge management and energy arbitrage, and in cases where battery degradation imposes a significant cost.

41 EE - Solar Energy Technologies Office (EE-4S)↗
DOE OSTI2019

Case Study of a Californian Brewery to Potentially Use Concentrating Solar Power for Renewable Heat Generation

With the increasing relevance and acceptance of solar thermal for industrial process heat (IPH), a case study for a proposed concentrating solar power (CSP) integration into an existing Californian brewery is highlighted. The thermal generation from a 1 MWth solar field was modelled in the System Advisor Model (SAM), and the economics considered the viability of the project where different variables such as the installed solar field cost were investigated on metrics such as Net Present Value (NPV) and payback period. For the Base Case, without the 30% Investment Tax Credit (ITC), and using a 2017 Federal income tax rate of 35%, the project’s NPV reached $0 (i.e., the project becomes viable), when the installed solar field cost reached $158/m2. With the 30% ITC and 35% tax, the solar field installed cost is estimated at $324/m2 to obtain an NPV = $0. The biggest influences on project viability measured by NPV were the project life, Federal tax rate, and the solar field cost.

case study↗
DOE OSTI2026

Technoeconomic Opportunity Analysis for Local Power Generation in Falls City, Nebraska

Falls City is a small community in Nebraska interested in understanding how energy from local energy systems could support the community's economic development planning. To address the current community needs and address the future energy demand technical assistance conducted through the Communities Local Energy Action Program (Communities LEAP) assessed the technical and economic opportunities of adding energy technologies to Falls City's municipally owned and operated electric utility system. The modeling performed considered the technical and economic feasibility of technologies using the System Advisor Model (SAM). The modeling explored three technology configurations using multiple years of historical weather and wholesale cost data (2015-2022 & a typical meteorological year), and two different wholesale escalation rates (0.3% and 2.5%). Wholesale energy prices were based on the Southwest Power Pool's (SPP) real-time energy market and the annual escalation rates of these rates based on historical SPP wholesale and national retail electricity price trends. Results from the modeling showed that at current CAPEX costs and SPP wholesale electricity costs no technology combination averaged across the scenarios run provide a positive net present value (NPV). External financial support, changes in market conditions, and additional revenue streams would help create more economically favorable projects. As conditions change re-evaluation may be necessary.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

DC-Connected Solar Plus Storage Modeling for Behind-the-Meter Systems in SAM

A detailed model for PV plus DC-connected batteries was developed. This model was compared to an existing AC connected 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 self consumption 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 OSTI2026

Powdermet CRADA for VELOCITI Voucher (CRADA Final Report)

NLR shall develop a model of an electric thermal energy storage (ETES) system in the System Advisor Model (SAM) framework that uses a salt and particle slurry developed by PowderMet as the thermal energy storage medium. The ETES shall consist of a recuperated sCO 2 Brayton cycle using 2-tank indirect thermal energy storage and an electric heater for heat input. The salt slurry uses chloride salt and operates at a maximum temperature of 500-720°C. The ETES uses dry air cooling. The salt slurry will be modeled as a sensible heat storage medium and as a latent heat storage medium. NLR will use the model to do parametric analysis of the factors affecting the performance (ex., round trip efficiency) of the ETES system. NLR will work with PowderMet to estimate the costs of system components and total system costs, with the levelized cost of electricity (LCOE) as the primary cost metric.

14 SOLAR ENERGY↗
DOE OSTI2022

Concentrated Solar Power as a Pathway for Electrolytic Hydrogen Production

William Xi and Mark Ruth of the National Renewable Energy Laboratory (NREL), will present a new solar-electrolysis technoeconomic assessment capability: low-temperature and high-temperature electrolysis in the System Advisor Model (SAM) environment. They will also present analysis results including opportunities for solar-hydrogen systems to achieve the $2/kg hydrogen cost target.

concentrating solar power↗
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

DC-connected Solar Plus Storage Modeling and Analysis for Behind-The-Meter Systems in the System Advisor Model: Preprint

A detailed model for PV plus DC-connected batteries was developed. This model was compared to an existing AC connected 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 self consumption 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 OSTI2024

Presenting a Model to Predict Changing Snow Albedo for Improving Photovoltaic Performance Simulation

As photovoltaic (PV) deployment increases worldwide, PV systems are being installed more frequently in locations that experience snow cover. The higher albedo of snow, relative to the ground, increases the performance of PV systems in northern and high-altitude locations by reflecting more light onto the PV modules. Accurate modeling of the snow’s albedo can improve estimates of PV system production. Typical modeling of snow albedo uses a simple two-value model that sets the albedo high when snow is present, and low when snow is not present. However, snow albedo changes over time as snow settles and melts and a binary model does not account for transitional changes, which can be significant. Here, we present and validate a model for estimating snow albedo as it changes over time. The model is simple enough to only require daily snow depth and hourly average temperature data, but can be improved through the addition of site-specific factors, when available. We validate this model to quantify its ability to more accurately predict snow albedo and compare the model’s performance against satellite imagery-based methods for obtaining historical albedo data. In addition, we perform modeling using the System Advisor Model (SAM) to show the impact of changes in albedo on energy modeling for PV systems. Overall, our albedo model has a significantly improved ability to predict the solar insolation on PV modules in real time, especially on bifacial PV modules where reflected irradiance plays a larger role in energy production.

Pike, Christopher (ORCID:0000000155888033)↗
DOE OSTI2023

Defining a compact dry cooler design to reduce LCOE contribution in a CSP facility

Concentrating solar power (CSP), when coupled with a supercritical carbon dioxide (sCO 2 ) power cycle and sensible heat storage, presents a renewable and clean alternative for utility-scale power generation. However, in order to be competitive in the current and future markets, CSP facilities must limit their levelized cost of electricity (LCOE) by minimizing capital costs and reducing operating costs over the lifetime of the plant. Targeting this goal, this study investigates the LCOE impact of the power cycle pre-cooler. This study considers a compact dry cooler with micro-channel technology on the CO 2 side and formed fin geometry on the air side, using directly-coupled centrifugal fans and a transition duct to improve air distribution across the fins as well as protect the fins from contaminants which may cause blockage, soiling, fouling, and damage. In an effort to better understand the dry cooler impact on LCOE, a sensitivity study was conducted using various combinations of end-to-end approach temperatures, air-side pressure drop values, CO 2 -side pressure drop values, fan types, cooler turndown control schemes, cooler module sizes, and design-point ambient temperatures. Furthemore, off-design cycle performance data was calculated for each dry cooler design using NPSS simulation software; cycle performance data were then input to System Advisor Model (SAM) along with the associated capital costs for LCOE prediction of a 100 MW system over a 30 year plant lifetime. Results of this study show the LCOE is most sensitive to air-side performance, followed by heat transfer effectiveness and capital cost. It was found that a power cycle with a mid- to high-performance dry cooler will produce the most competitive power-production costs. Designing at the extreme ends for approach temperature (or effectiveness), design-point ambient temperature, and compactness (footprint) produce higher LCOE values; mid-range values for these parameters balance performance, operating costs, and associated capital cost to optimize LCOE.

14 SOLAR ENERGY↗
DOE OSTI2018

Evaluating Energy Impacts and Costs from PV Component Failures: Preprint

The PV Reliability Performance Model (PV-RPM) tool is used to simulate the cost and energy impacts of component faults and failures for a hypothetical PV system. This model, originally developed by Sandia National Laboratories, is a new feature in the National Renewable Energy Laboratory's System Advisor Model (SAM), which performs stochastic analysis sampling of probability distributions for faults, failures, and repairs. One PV system was created for this analysis to be representative of a portfolio of maintenance data maintained by Sandia National Laboratories. Fault, failure, and repair distributions from this system are varied from current baseline conditions to simulate different reliability and repair scenarios and resulting energy and cost impacts. Results highlight ways to express the uncertainty around PV system performance when considering the probabilistic behavior of components in the system, and ways the PV-RPM model can be used to explore different failure and repair scenarios.

14 SOLAR ENERGY↗
DOE OSTI2018

Evaluating Energy Impacts and Costs from PV Component Failures

The PV Reliability PerformanceModel (PV-RPM) tool is used to simulate the cost and energy impacts of component faults and failures for a hypothetical PV system. This model, originally developed by Sandia National Laboratories, is a new feature in the National Renewable Energy Laboratory's System Advisor Model (SAM), which performs stochastic analysissampling of probability distributions for faults, failures, and repairs. One PV system was created for this analysis to be representative of a portfolio of maintenance data maintained by Sandia National Laboratories. Fault,failure, and repair distributions from this system are varied from current baseline conditions to simulate different reliability and repair scenarios and resulting energy and cost impacts. Results highlight ways to express the uncertainty around PV system performance when considering the probabilistic behavior of components inthe system, and ways the PV-RPM model can be used to explore different failure and repair scenarios.

14 SOLAR ENERGY↗