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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 19 records

Evaluating the Value of High Spatial Resolution in National Capacity Expansion Models using ReEDS

Power sector capacity expansion models (CEMs) have a broad range of spatial resolutions. This paper uses the Regional Energy Deployment System (ReEDS) model, a long-term national scale electric sector CEM, to evaluate the value of high spatial resolution for CEMs. ReEDS models the United States with 134 load balancing areas (BAs) and captures the variability in existing generation parameters, future technology costs, performance, and resource availability using very high spatial resolution data, especially for wind and solar modeled at 356 resource regions. In this paper we perform planning studies at three different spatial resolutions--native resolution (134 BAs), state-level, and NERC region level--and evaluate how results change under different levels of spatial aggregation in terms of renewable capacity deployment and location, associated transmission builds, and system costs. The results are used to ascertain the value of high geographically resolved models in terms of their impact on relative competitiveness among renewable energy resources.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Lignocellulosic crop supply chains (eg, Miscanthus, switchgrass, reed canary grass, rye, giant reed, etc.) Chapter 12 of "Biomass Supply Chains for Bioenergy and Biorefining"

This chapter provides an overview of lignocellulosic crop supply chains such as Miscanthus, switch grass, reed canary grass, rye, and giant reed by outlining typical logistic operations in support of a liquid biofuel market. We present two strategies for managing feedstocks within the biomass supply system: (1) the conventional bale feedstock supply system and (2) the advanced supply system concept. Finally, we discuss feedstock blending and integrated landscape management as innovative improvements to the lignocellulosic crop supply chain.

09 BIOMASS FUELS↗

Adjustable reed for weaving net-shaped tailored fabrics

The invention is an apparatus and method for forming woven fabrics through the use of an adjustable reed. The adjustable reed has multiple groups of reed wires that guide the warp yarns. The groups of reed wires move on reed rails parallel to the warp direction. In addition, rail expanders permit the space between the reed wires to be modified and telescoping rods attached to the rail sliders can be turned to permit the reed wires to be skewed to alter the fill yarn angle. These adjustments to the reed permit simultaneous variation of fill yarn angles and fabric widths and allow these variations to be made during fabrication, without the need to halt production.

Farley, Gary L.↗

Adjustable reed for weaving net-shaped tailored fabrics

An apparatus and method for forming woven fabrics through the use of an adjustable reed. The adjustable reed has multiple groups of reed wires that guide the warp yarns. The groups of reed wires move on reed rails parallel to the warp direction. In addition, rail expanders permit the space between the reed wires to be modified and telescoping rods attached to the rail sliders can be turned to permit the reed wires to be skewed to alter the fill yarn angle. These adjustments to the reed permit simultaneous variation of fill yarn angles and fabric widths and allow these variations to be made during fabrication, without the need to halt production.

Farley, Gary L.↗

Historical Comparison of Capacity Build Decisions from the Regional Energy Deployment System (ReEDS) Model

The Regional Energy Deploy System (ReEDS) capacity expansion model is frequently used to project the evolution of the U.S. power sector under a wide range of conditions. However, the model's capacity expansion decisions have never been evaluated against historical capacity expansion decisions. In this work, we perform a model validation exercise, comparing capacity expansion decision from ReEDS for 2010-2016 against the actual buildout of the electricity sector. We find that with three key adjustments ReEDS is able to reproduce national level results with reasonably high accuracy. Those three adjustments are to use historical average planning reserve margins instead of the NERC-recommended reserve margin levels, using actual financing costs rather than long-term average financing costs, and disallowing the lowest-cost hydropower upgrades, geothermal sites, and compress-air energy storage sites. We also compare the ReEDS results at a state-level and find that state-level results can be better represented by including a penalty for transferring power between regions. The improved results with that penalty indicate that the ReEDS transmission representation is likely not sufficiently stringent, and should be improved. Overall these results show that with the improvements described above, ReEDS can effectively reproduce historical capacity additions, which increases our confidence in using the model in making forward-looking projections.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Adjustable Reeds For Weaving

Local characteristics of fabrics varied to suit special applications. Adjustable reed machinery proposed for use in weaving fabrics in various net shapes, widths, yarn spacings, and yarn angles. Locations of edges of fabric and configuration of warp and filling yarns varied along fabric to obtain specified properties. In machinery, reed wires mounted in groups on sliders, mounted on lengthwise rails in reed frame. Mechanisms incorporated to move sliders lengthwise, parallel to warp yarns, by sliding them along rails; move sliders crosswise by translating reed frame rails perpendicular to warp yarns; and crosswise by spreading reed rails within group. Profile of reed wires in group on each slider changed.

Farley, Gary L.↗

County-Level Hourly Renewable Capacity Factor Dataset for the ReEDS Model

This dataset contains hourly capacity factors for each renewable resource class and region (in this case, county). Technologies like large-scale utility PV (UPV), onshore wind, offshore wind, and concentrating solar power (CSP) are included. The dataset contains 7 years of hourly weather data (2007-2013) for different sites across the US and is used as one of the inputs to the ReEDS-2.0 model (see the "ReEDS 2.0 GitHub Repository" resource link below), developed by NREL. The weather profiles apply to any capacity that exists or is built in each region and class. This helps calculate the generation that can be provided using these resources. Open, reference, and limited are 3 scenarios based on land-use allowance, derived from the Renewable Energy Potential (reV) model developed by NREL, which helps generate supply curves for renewable technologies and assess the maximum potential of renewable resources in a designated area. Each zipped file in this dataset corresponds to a technology and contains the respective land-use scenario files required to run that technology in ReEDS. To use this dataset, download and place the extracted files in the locally cloned ReEDS repository inside one of the folders (inputs/variability/multi_year). After completing this copy, upon running the ReEDS model at the county-level spatial resolution for respective analysis purposes, the program will detect the presence of these files and will not fail.

Array↗

ReEDS Performance Improvement

The Regional Energy Deployment System (ReEDS) is an open-source, spatially explicit, long-term capacity expansion model for the bulk electric power system of the contiguous United States, encompassing multiple scenarios with technological and political assumptions (see https://github.com/NREL/ReEDS-2.0). With the increased needs for capabilities, higher temporal and spatial resolutions to model the evolution of the power system with modern technologies and low-carbon pathways, ReEDS' model solution times have increased significantly from 4-6 hours in 2018 to 18-48+ hours in 2023 . Also, the model size for commonly-run ReEDS scenarios reached 22 and 28 million equations and variables, respectively. These runtimes can be especially challenging under certain scenario settings (e.g., very high temporal or spatial resolution) or with limited computational power. In this presentation, we will discuss several methods we used to improve model runtime, including data preparation, model modification, and solver tuning. The implementation of these methods shrank the model size to 7.2 and 7.3 million equations and variables, respectively. Furthermore, this led to a 77% reduction in the model's run time for commonly-run ReEDS scenarios. We will discuss the process of identifying areas for solve time improvements and how the specific enhancements for the ReEDS model might be applied to other similar large-scale models.

ENERGY PLANNING, POLICY, AND ECONOMY,MATHEMATICS A↗

Exploiting the cannibalistic traits of Reed-Solomon codes

In Reed-Solomon codes and all other maximum distance separable codes, there is an intrinsic relationship between the size of the symbols in a codeword and the length of the codeword. Increasing the number of symbols in a codeword to improve the efficiency of the coding system thus requires using a larger set of symbols. However, long Reed-Solomon codes are difficult to implement and many communications or storage systems cannot easily accommodate an increased symbol size, e.g., M-ary frequency shift keying (FSK) and photon-counting pulse-position modulation demand a fixed symbol size. A technique for sharing redundancy among many different Reed-Solomon codewords to achieve the efficiency attainable in long Reed-Solomon codes without increasing the symbol size is described. Techniques both for calculating the performance of these new codes and for determining their encoder and decoder complexities is presented. These complexities are usually found to be substantially lower than conventional Reed-Solomon codes of similar performance.

Collins, O.↗

ReEDS-Mexico: A Capacity Expansion Model of the Mexican Power System

This report documents the ReEDS-Mexico capacity expansion model, which is an extension of the ReEDS model to the Mexican power system. In recent years Mexico’s power sector has undergone considerable reform that has significant potential to impact the future electricity mix (Alpizar–Castro and Rodríguez–Monroy 2016). Day-ahead and real-time trading in Mexico’s power markets opened in early 2016. In addition to this reform, Mexico is striving to ensure that 35% of its electricity is generated from clean energy sources by 2024, 40% by 2035, and 50% by 2050 (Presidencia de la República 2016). These rapid changes in both the market and the generation mix create a need for robust tools that can help electricity sector stakeholders make informed decisions. The purpose of this report is to document the extension of the National Renewable Energy Laboratory’s (NREL’s) Regional Energy Deployment System (ReEDS) model (Eurek et al. 2016) to cover the Mexico power system. This extension, which we will refer to throughout this paper as ReEDS-Mexico, provides a model of the Mexico power sector using a system-wide, least-cost optimization framework.

14 SOLAR ENERGY↗

Assessment of Methods to Control Invasive Reed Canarygrass (Phalaris arundinacea) in Tidal Freshwater Wetlands

Controlling non-native invasive species is a significant challenge facing natural area managers in North America and around the world. Reed canarygrass (Phalaris arundinacea), is invasive in temperate freshwater wetlands throughout the United States and Canada. While methods for the prevention or elimination of reed canarygrass are generally well established, methods suitable for the unique conditions in tidal wetlands remain poorly understood. Namely, prolonged inundation of tidal wetlands for control purposes may only be accomplished with a concomitant loss of habitat connectivity and other functions. Restoration practitioners aiming to design self-sustaining wetlands in the lower Columbia River and estuary, on the northwestern Pacific Coast, have found that reed canarygrass is widespread and quick to establish throughout the 176-river-kilometer tidal freshwater floodplain. Here we report the results of a comprehensive effort to develop the knowledge base for control in tidal wetlands, through systematic review of the scientific literature, interviews with experienced practitioners, and field observations at nine Pacific Northwest sites. The review framework incorporated practical considerations and key environmental conditions: elevation related to hydrologic regime, salinity, shade, and nutrient availability. The results support implementation of multiple methods for a minimum of five years, on the largest possible area, ideally the watershed scale. Applicable methods include control in advance of restoration, topographic modification such as scrape-downs and mounds; establishing strong native competitors; and periodic, targeted control. Formal field experiments are needed to evaluate factors that influence control. Developing science-based, effective, practicable approaches to control reed canarygrass should improve restoration outcomes in natural areas.

intertidal, invasive, Phalaris arundinacea, reed c↗

ReEDS™ 2.0 Model (Regional Energy Deployment System Model) Version 2.0 [SWR-20-36 and SWR-09-14]

ReEDS™ is a capacity planning and dispatch model for the U.S. electricity system. As the National Laboratory of the Rockies (NLR's) flagship long-term power sector model, ReEDS has served as the primary analytic tool for many studies of electricity sector research questions. Example model results are available in the Scenario Viewer here: https://scenarioviewer.nlr.gov/. Quick-start guide The ReEDS model is written in Python, GAMS, and Julia. Python and Julia are free, open-source languages; GAMS requires a software license from the vendor. A step-by-step guide for getting started with ReEDS is available here: https://pages.github.nrel.gov/ReEDS/ReEDS-2.0/setup.html.

Short, Walter↗

Erasure information for a Reed-Solomon decoder

Many Reed-Solomon decoders, including the one decoding the outer code for Voyager data from Uranus, assume that all symbols have the same chance of being correct or incorrect. Insome cases, like in a burst of incorrect symbols, this is not the case, and a Reed-Solomon decoder could make use of this. The use of information about bit quality sent to the Reed-Solomon from an (inner) Viterbi decoder is examined, as well as information about the error status of adjacent symbols in decoding interleaved Reed-Solomon encoded symbols. It is discovered that, in a region of interest, only about 0.04 dB can gained.

Pitt, G. H., III↗

Burst error correction extensions for large Reed Solomon codes

Reed Solomon codes are powerful error correcting codes that include some of the best random and burst correcting codes currently known. It is well known that an (n,k) Reed Solomon code can correct up to (n - k)/2 errors. Many applications utilizing Reed Solomon codes require corrections of errors consisting primarily of bursts. In this paper, it is shown that the burst correcting ability of Reed Solomon codes can be increased beyond (n - k)/2 with an acceptable probability of miscorrect.

Owsley, P.↗

Renewable Energy Potential Model: Priority Geothermal Leasing Areas ReEDs Results

This dataset contains the results of a study conducted by the National Renewable Energy Laboratory (NREL) to identify potential future priority geothermal leasing areas on Bureau of Land Management (BLM) and United States Forest Service (USFS) lands. The analysis uses the Regional Energy Deployment System (ReEDS) model to evaluate geothermal resource potential under different scenarios of resource depth and technology combinations through the year 2050. The study considers geothermal resource potential, natural resource conflicts, and transmission access to categorize areas into near, mid, and far deployment priorities. The dataset includes outputs from the ReEDS model, such as geothermal capacity, generation, system costs, and emissions under various economic and technical scenarios. Favorability site data with geographic coordinates and site-specific attributes (e.g., resource favorability, land type) are also provided. Supporting resources include a technical report detailing methodologies and assumptions, along with a link to the ReEDS model GitHub repository, which requires GAMS and Python software for execution.

15 GEOTHERMAL ENERGY↗

A Tutorial for Using an Open-Source Solver for the Regional Energy Deployment System (ReEDS) Model

ReEDS is a publicly available model developed at NREL that can be used to analyze the potential evolution of the U.S. electric power system into the future. ReEDS is formulated as a linear program, written in GAMS, and solved using a linear programming solver (e.g., CPLEX). This tutorial provides context and understanding for the implications of using an open-source solver for ReEDS.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Operating Reserves in ReEDS

This presentation provides an overview of the formulation for operating reserves in the Regional Energy Deployment System (ReEDS), a capacity expansion model. It describes the three reserve products modeled in ReEDS--regulation, spinning (contingency), and flexibility--and highlights recent updates to the modeling approach, including modifications to how storage provides reserves, the constraints on commitment for generators that provide reserves, and the costs for thermal units to provide spinning reserve. The presentation benchmarks operating reserve provision in ReEDS against comparable simulations in PLEXOS, finding that the improved formulation is different but yields results that are holistically similar to those in production cost modeling. In this presentation we also investigate the impact of different reserve options in the model (e.g., allowing wind and solar to provide operating reserves) on the solution. The results thus far indicate that most switches related to operating reserves exert little influence on the outcome on the results. Future work will continue to explore operating reserves in capacity expansion models, particularly for models with different temporal resolution.

14 SOLAR ENERGY↗

A comparison of VLSI architectures for time and transform domain decoding of Reed-Solomon codes

It is well known that the Euclidean algorithm or its equivalent, continued fractions, can be used to find the error locator polynomial needed to decode a Reed-Solomon (RS) code. It is shown that this algorithm can be used for both time and transform domain decoding by replacing its initial conditions with the Forney syndromes and the erasure locator polynomial. By this means both the errata locator polynomial and the errate evaluator polynomial can be obtained with the Euclidean algorithm. With these ideas, both time and transform domain Reed-Solomon decoders for correcting errors and erasures are simplified and compared. As a consequence, the architectures of Reed-Solomon decoders for correcting both errors and erasures can be made more modular, regular, simple, and naturally suitable for VLSI implementation.

Hsu, I. S.↗