Engineering topics

Lopez, Anthony

Publications and source records attributed to Lopez, Anthony.

At least 55 records · Page 3

DOE OSTI2017

An improved global wind resource estimate for integrated assessment models

This study summarizes initial steps to improving the robustness and accuracy of global renewable resource and techno-economic assessments for use in integrated assessment models. We outline a method to construct country-level wind resource supply curves, delineated by resource quality and other parameters. Using mesoscale reanalysis data, we generate estimates for wind quality, both terrestrial and offshore, across the globe. Because not all land or water area is suitable for development, appropriate database layers provide exclusions to reduce the total resource to its technical potential. We expand upon estimates from related studies by: using a globally consistent data source of uniquely detailed wind speed characterizations; assuming a non-constant coefficient of performance for adjusting power curves for altitude; categorizing the distance from resource sites to the electric power grid; and characterizing offshore exclusions on the basis of sea ice concentrations. The product, then, is technical potential by country, classified by resource quality as determined by net capacity factor. Additional classifications dimensions are available, including distance to transmission networks for terrestrial wind and distance to shore and water depth for offshore. We estimate the total global wind generation potential of 560 PWh for terrestrial wind with 90% of resource classified as low-to-mid quality, and 315 PWh for offshore wind with 67% classified as mid-to-high quality. These estimates are based on 3.5 MW composite wind turbines with 90 m hub heights, 0.95 availability, 90% array efficiency, and 5 MW/km 2 deployment density in non-excluded areas. We compare the underlying technical assumption and results with other global assessments.

17 WIND ENERGY↗

DOE OSTI2017

It's Indisputable: Five Facts About Planning and Operating Modern Power Systems

An indisputable fact cannot be rebutted. It is supported by theory and experience. Over the past 25 years, wind and solar generation has undergone dramatic growth, resulting in a variety of experiences that model the integration of wind and solar into the planning and operation of modern electric power systems. In this article, we bring together examples from Europe, North America, and Australia to identify five indisputable facts about planning and operating modern power systems. Taken together, we hope these experiences can help build consensus among the engineering and public policy communities about the current state of wind and solar integration and also facilitate conversations about evolving future challenges.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2017

The National Solar Radiation Database (NSRDB): A Brief Overview

This poster presents a high-level overview of the National Solar Radiation Database (NSRDB). The NSRDB uses the physics-based model (PSM), which was developed using: adapted PATMOS-X model for cloud identification and properties, REST-2 model for clear-sky conditions, and NREL's Fast All-sky Radiation Model for Solar Applications (FARMS) for cloudy-sky Global Horizontal Irradiance (GHI) solar irradiance calculations.

14 SOLAR ENERGY↗

DOE OSTI2017

Capturing Inter-Annual Variability of PV Energy Production in South Asia

Long-term variability of solar resource is an important factor in planning a utility-scale photovoltaic (PV) generation plant, and annual generation for a given location can vary significantly from year to year. Based on multiple years of solar irradiance data, an exceedance probability is the amount of energy that could potentially be produced by a power plant in any given year. An exceedance probability accounts for long-term variability and climate cycles (e.g., monsoons or changes in aerosols), which ultimately impact PV energy generation. Study results indicate that a significant bias could be associated with relying solely on typical meteorological year (TMY) resource data to capture long-term variability. While the TMY tends to under-predict annual generation overall compared to the P50, there appear to be pockets of over-prediction as well.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2017

Use of MERRA-2 in the National Solar Radiation Database and Beyond

The National Solar Radiation Database (NSRDB) is a flagship product of NREL that provides solar radiation and ancillary meteorological information through a GIS based portal. This data is provided at a 4kmx4km spatial and 30 minute temporal resolution covering the period between 1998-2015. The gridded data that is distributed by the NSRDB is derived from satellite measurements using the Physical Solar Model (PSM) that contains a 2-stage approach. This 2-stage approach consists of first retrieving cloud properties using measurement from the GOES series of satellites and using that information in a radiative transfer model to estimate solar radiation at the surface. In addition to the satellite data the model requires ancillary meteorological information that is provided mainly by NASA's Modern Era Retrospecitve Analysis for Research and Applications (MERRA-2) 2 model output. This presentation provides an insight into how the NSRDB is developed using the PSM and how the various sources of data including the MERRA-2 data is used during the process.

14 SOLAR ENERGY↗

DOE OSTI2017

Understanding the Temporal and Spatial Variability of New Generation Gridded TMYs

Presentation at ASHRAE about the spatial and temporal variability of gridded TMYs, discussing advanced GIS and Web services that allow for direct access to data, surface-based observations for thousands of stations, climate reanalysis data, and products derived from satellite data; new developments in NREL's solar databases based on both observed data and satellite-derived gridded data, status of TMY3 weather files, and NREL's plans for the next-generation TMY weather files; and also covers what is new and different in the Climatic Design Conditions Table in the 2013 ASHRAE Handbook of Fundamentals.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2017

Evaluation of the National Solar Radiation Database (NSRDB): 1998-2015

This paper validates the performance of the physics-based Physical Solar Model (PSM) data set in the National Solar Radiation Data Base (NSRDB) to quantify the accuracy of the magnitude and the spatial and temporal variability of the solar radiation data. Achieving higher penetrations of solar energy on the electric grid and reducing integration costs requires accurate knowledge of the available solar resource. Understanding the impacts of clouds and other meteorological constituents on the solar resource and quantifying intra-/inter-hour, seasonal, and interannual variability are essential for accurately designing utility-scale solar energy projects. Solar resource information can be obtained from ground-based measurement stations and/or from modeled data sets. The availability of measurements is scarce, both temporally and spatially, because it is expensive to maintain a high-density solar radiation measurement network that collects good quality data for long periods of time. On the other hand, high temporal and spatial resolution gridded satellite data can be used to estimate surface radiation for long periods of time and is extremely useful for solar energy development. Because of the advantages of satellite-based solar resource assessment, the National Renewable Energy Laboratory developed the PSM. The PSM produced gridded solar irradiance -- global horizontal irradiance (GHI), direct normal irradiance (DNI), and diffuse horizontal irradiance -- for the NSRDB at a 4-km by 4-km spatial resolution and half-hourly temporal resolution covering the 18 years from 1998-2015. The NSRDB also contains additional ancillary meteorological data sets, such as temperature, relative humidity, surface pressure, dew point, and wind speed. Details of the model and data are available at https://nsrdb.nrel.gov. The results described in this paper show that the hourly-averaged satellite-derived data have a systematic (bias) error of approximately +5% for GHI and less than +10% for DNI; however, the scatter (root mean square error [RMSE]) difference is higher for the hourly averages.

14 SOLAR ENERGY↗

DOE OSTI2017

Evaluation of the National Solar Radiation Database (NSRDB): 1998-2015

14 SOLAR ENERGY↗

DOE OSTI2017

The National Solar Radiation Database (NSRDB)

This presentation provides a high-level overview of the National Solar Radiation Database (NSRDB), including sensing, measurement and forecasting, and discusses observations that are needed for research and product development.

14 SOLAR ENERGY↗

DOE OSTI2017

An Improved Global Wind Resource Estimate for Integrated Assessment Models: Preprint

This paper summarizes initial steps to improving the robustness and accuracy of global renewable resource and techno-economic assessments for use in integrated assessment models. We outline a method to construct country-level wind resource supply curves, delineated by resource quality and other parameters. Using mesoscale reanalysis data, we generate estimates for wind quality, both terrestrial and offshore, across the globe. Because not all land or water area is suitable for development, appropriate database layers provide exclusions to reduce the total resource to its technical potential. We expand upon estimates from related studies by: using a globally consistent data source of uniquely detailed wind speed characterizations; assuming a non-constant coefficient of performance for adjusting power curves for altitude; categorizing the distance from resource sites to the electric power grid; and characterizing offshore exclusions on the basis of sea ice concentrations. The product, then, is technical potential by country, classified by resource quality as determined by net capacity factor. Additional classifications dimensions are available, including distance to transmission networks for terrestrial wind and distance to shore and water depth for offshore. We estimate the total global wind generation potential of 560 PWh for terrestrial wind with 90% of resource classified as low-to-mid quality, and 315 PWh for offshore wind with 67% classified as mid-to-high quality. These estimates are based on 3.5 MW composite wind turbines with 90 m hub heights, 0.95 availability, 90% array efficiency, and 5 MW/km2 deployment density in non-excluded areas. We compare the underlying technical assumption and results with other global assessments.

17 WIND ENERGY↗

DOE OSTI2016

High-Level Overview of Data Needs for RE Analysis

This presentation provides a high level overview of analysis topics and associated data needs. Types of renewable energy analysis are grouped into two buckets: First, analysis for renewable energy potential, and second, analysis for other goals. Data requirements are similar but and they build upon one another.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2016

Navajo Generating Station and Federal Resource Planning; Volume 1: Sectoral, Technical, and Economic Trends

This study for the U.S. Bureau of Reclamation examines conditions in the electricity sector that are likely to affect federal decisions with respect to Navajo Generating Station (NGS), the largest coal-fired power plant operating in the western United States. The federal government owns 24.3% of the 2.25-gigawatt plant, which amounts to 547 megawatts (MW) of capacity. By focusing on the unique public interests that depend on the federal share of NGS, this baseline study can help the federal government develop a road map for meeting all of its goals with respect to water delivery, clean energy, emission reduction, and economic development. There is no recommendation for action in this report. Rather, its aim is to provide a credible, thorough description of baseline conditions that might affect federal decisions regarding NGS. It describes facts and trends embedded in current data, but there are no conclusions about how Reclamation or DOI should respond to the trends. The interdependencies among the many sectoral trends and federal goals are complex, and the aim of this study is to provide a foundation from which options can be tested in a deliberate manner.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2016

Estimating Renewable Energy Economic Potential in the United States. Methodology and Initial Results

This report describes a geospatial analysis method to estimate the economic potential of several renewable resources available for electricity generation in the United States. Economic potential, one measure of renewable generation potential, may be defined in several ways. For example, one definition might be expected revenues (based on local market prices) minus generation costs, considered over the expected lifetime of the generation asset. Another definition might be generation costs relative to a benchmark (e.g., a natural gas combined cycle plant) using assumptions of fuel prices, capital cost, and plant efficiency. Economic potential in this report is defined as the subset of the available resource technical potential where the cost required to generate the electricity (which determines the minimum revenue requirements for development of the resource) is below the revenue available in terms of displaced energy and displaced capacity. The assessment is conducted at a high geospatial resolution (more than 150,000 technology-specific sites in the continental United States) to capture the significant variation in local resource, costs, and revenue potential. This metric can be a useful screening factor for understanding the economic viability of renewable generation technologies at a specific location. In contrast to many common estimates of renewable energy potential, economic potential does not consider market dynamics, customer demand, or most policy drivers that may incent renewable energy generation.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2016

Estimating Renewable Energy Economic Potential in the United States: Methodology and Initial Results

The report describes a geospatial analysis method to estimate the economic potential of several renewable resources available for electricity generation in the United States. Economic potential, one measure of renewable generation potential, is defined in this report as the subset of the available resource technical potential where the cost required to generate the electricity (which determines the minimum revenue requirements for development of the resource) is below the revenue available in terms of displaced energy and displaced capacity.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2016

India Direct Normal & Global Horizontal Irradiance Solar Resources

GIS data for India's direct normal irradiance (DNI) and global horizontal irradiance. Provides 10-kilometer (km) solar resource maps and data for India. The 10-km hourly solar resource data were developed using weather satellite (METEOSAT) measurements incorporated into a site-time specific solar modeling approach developed at the U.S. State University of New York at Albany. The data is made publicly available in geographic information system (GIS) format (shape files etc). The new maps and data were released in June 2013. The new data expands the time period of analysis from 2002-2007 to 2002-2011 and incorporates enhanced aerosols information to improve direct normal irradiance (DNI). These products were developed by the U.S. National Renewable Energy Laboratory (NREL) in cooperation with India's Ministry of New and Renewable Energy, through funding from the U.S. Department of Energy and U.S. Department of State.

10-kilometer↗

DOE OSTI2015

Screening tool to evaluate the vulnerability of down-gradient receptors to groundwater contaminants from uncapped landfills

Highlights: • A spreadsheet-based risk screening tool for groundwater affected by landfills is presented. • Domenico solute transport equations are used to estimate downgradient contaminant concentrations. • Landfills are categorized as presenting high, moderate or low risks. • Analysis of parameter sensitivity and examples of the method’s application are given. • The method has value to regulators and those considering redeveloping closed landfills. - Abstract: A screening tool for quantifying levels of concern for contaminants detected in monitoring wells on or near landfills to down-gradient receptors (streams, wetlands and residential lots) was developed and evaluated. The tool uses Quick Domenico Multi-scenario (QDM), a spreadsheet implementation of Domenico-based solute transport, to estimate concentrations of contaminants reaching receptors under steady-state conditions from a constant-strength source. Unlike most other available Domenico-based model applications, QDM calculates the time for down-gradient contaminant concentrations to approach steady state and appropriate dispersivity values, and allows for up to fifty simulations on a single spreadsheet. Sensitivity of QDM solutions to critical model parameters was quantified. The screening tool uses QDM results to categorize landfills as having high, moderate and low levels of concern, based on contaminant concentrations reaching receptors relative to regulatory concentrations. The application of this tool was demonstrated by assessing levels of concern (as defined by the New Jersey Pinelands Commission) for thirty closed, uncapped landfills in the New Jersey Pinelands National Reserve, using historic water-quality data from monitoring wells on and near landfills and hydraulic parameters from regional flow models. Twelve of these landfills are categorized as having high levels of concern, indicating a need for further assessment. This tool is not a replacement for conventional numerically-based transport model or other available Domenico-based applications, but is suitable for quickly assessing the level of concern posed by a landfill or other contaminant point source before expensive and lengthy monitoring or remediation measures are taken. In addition to quantifying the level of concern using historic groundwater-monitoring data, the tool allows for archiving model scenarios and adding refinements as new data become available.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2015

Validation of the National Solar Radiation Database (NSRDB) (2005-2012): Preprint

Publicly accessible, high-quality, long-term, satellite-based solar resource data is foundational and critical to solar technologies to quantify system output predictions and deploy solar energy technologies in grid-tied systems. Solar radiation models have been in development for more than three decades. For many years, the National Renewable Energy Laboratory (NREL) developed and/or updated such models through the National Solar Radiation Data Base (NSRDB). There are two widely used approaches to derive solar resource data from models: (a) an empirical approach that relates ground-based observations to satellite measurements and (b) a physics-based approach that considers the radiation received at the satellite and creates retrievals to estimate clouds and surface radiation. Although empirical methods have been traditionally used for computing surface radiation, the advent of faster computing has made operational physical models viable. The Global Solar Insolation Project (GSIP) is an operational physical model from the National Oceanic and Atmospheric Administration (NOAA) that computes global horizontal irradiance (GHI) using the visible and infrared channel measurements from the Geostationary Operational Environmental Satellites (GOES) system. GSIP uses a two-stage scheme that first retrieves cloud properties and then uses those properties in the Satellite Algorithm for Surface Radiation Budget (SASRAB) model to calculate surface radiation. NREL, the University of Wisconsin, and NOAA have recently collaborated to adapt GSIP to create a high temporal and spatial resolution data set. The product initially generates the cloud properties using the AVHRR Pathfinder Atmospheres-Extended (PATMOS-x) algorithms [3], whereas the GHI is calculated using SASRAB. Then NREL implements accurate and high-resolution input parameters such as aerosol optical depth (AOD) and precipitable water vapor (PWV) to compute direct normal irradiance (DNI) using the DISC model. The AOD and PWV, temperature, and pressure data are also combined with the MMAC model to simulate solar radiation under clear-sky conditions. The current NSRDB update is based on a 4-km x 4-km resolution at a 30-minute time interval, which has a higher temporal and spatial resolution. This paper demonstrates the evaluation of the data set using ground-measured data and detailed evaluation statistics. The result of the comparison shows a good correlation to the NSRDB data set. Further, an outline of the new version of the NSRDB and future plans for enhancement and improvement are provided.

14 SOLAR ENERGY↗

DOE OSTI2015

Methodology for Clustering High-Resolution Spatiotemporal Solar Resource Data

In this report, we introduce a methodology to achieve multiple levels of spatial resolution reduction of solar resource data, with minimal impact on data variability, for use in energy systems modeling. The selection of an appropriate clustering algorithm, parameter selection including cluster size, methods of temporal data segmentation, and methods of cluster evaluation are explored in the context of a repeatable process. In describing this process, we illustrate the steps in creating a reduced resolution, but still viable, dataset to support energy systems modeling, e.g. capacity expansion or production cost modeling. This process is demonstrated through the use of a solar resource dataset; however, the methods are applicable to other resource data represented through spatiotemporal grids, including wind data. In addition to energy modeling, the techniques demonstrated in this paper can be used in a novel top-down approach to assess renewable resources within many other contexts that leverage variability in resource data but require reduction in spatial resolution to accommodate modeling or computing constraints.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗