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DOE OSTI2016

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↗

DOE OSTI2016

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↗

DOE OSTI2019

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↗

DOE OSTI2011

Engine Cycle Analysis of Air Breathing Microwave Rocket with Reed Valves

The Microwave Rocket is a candidate for a low cost launcher system. Pulsed plasma generated by a high power millimeter wave beam drives a blast wave, and a vehicle acquires impulsive thrust by exhausting the blast wave. The thrust generation process of the Microwave Rocket is similar to a pulse detonation engine. In order to enhance the performance of its air refreshment, the air-breathing mechanism using reed valves is under development. Ambient air is taken to the thruster through reed valves. Reed valves are closed while the inside pressure is high enough. After the time when the shock wave exhausts at the open end, an expansion wave is driven and propagates to the thrust-wall. The reed valve is opened by the negative gauge pressure induced by the expansion wave and its reflection wave. In these processes, the pressure oscillation is important parameter. In this paper, the pressure oscillation in the thruster was calculated by CFD combined with the flux through from reed valves, which is estimated analytically. As a result, the air-breathing performance is evaluated using Partial Filling Rate (PFR), the ratio of thruster length to diameter L/D, and ratio of opening area of reed valves to superficial area {alpha}. An engine cycle and predicted thrust was explained.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2023

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↗

DOE OSTI2013

Physiological and morphological effects of high water tables on early growth of giant reed ( Arundo donax ), elephant grass ( Pennisetum purpureum ), energycane and sugarcane ( Saccharum spp. )

Here, an increasing demand for renewable energy sources has spurred interest in high-biomass crops used for energy production. Species potentially well-suited for biofuel production in the seasonally wet organic Everglades Agricultural Area (EAA) of Florida include giant reed ( Arundo donax ), elephant grass ( Pennisetum Purpureum ), energycane ( Saccharum spp. ), and sugarcane ( Saccharum spp. ). The objectives in this study were to evaluate the role of fluctuating water tables on the morphology, physiology, and early season growth of these four genotypes. The candidate genotypes were grown in a greenhouse under three water table depths, defined by distance of the water table from the soil surface: two constant water tables (-16 cm and -40 cm) along with a flood cycle (2 weeks of flood to the soil level followed by 2 weeks at -40 cm from the soil level). The genotypes included CP 89-2143 (sugarcane), L 79-1002 (energycane), Merkeron (elephant grass), and wild type (giant reed). The experiment was repeated for plant cane, first ratoon, and successive plant cane crop cycles. Reductions in dry matter yield were observed among genotypes subjected to the -40 cm drained, periodically flooded (40F) water table relative to the -40 cm constant (40C) or -16 cm constant (16C). Plant cane dry weights were reduced by 37% in giant reed, 52% in elephant grass, 42% in energycane, and 34% in sugarcane in the 40F compared to 40C water table treatments. Similarly, in the first ratoon crop dry weights were reduced by 29% in giant reed, 42% in elephant grass, 27% in energycane, and 62% in sugarcane. In plant cane and successive plant cane, average total dry weight was greatest for elephant grass whereas ratoon total dry weight was greatest for energycane. Genotype had more pronounced effects on physiological attributes than water table including the highest stomatal conductance and SPAD values in giant reed, and the highest stalk populations in elephant grass and energycane. Aerenchyma presence and volume increased under higher water tables with elephant grass having the greatest aerenchyma production. Because of the high yields and stalk populations in energycane and elephant grass for all crop stages seen in this study, these two genotypes show potential for bioenergy production in the EAA, but field trials are recommended to confirm this.

09 BIOMASS FUELS↗

DOE OSTI2024

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↗

DOE OSTI2013

Integrated Canada-U.S. Power Sector Modeling with the Regional Energy Deployment System (ReEDS)

The electric power system in North America is linked between the United States and Canada. Canada has historically been a net exporter of electricity to the United States. The extent to which this remains true will depend on the future evolution of power markets, technology deployment, and policies. To evaluate these and related questions, we modify the Regional Energy Deployment System (ReEDS) model to include an explicit representation of the grid-connected power system in Canada to the continental United States. ReEDS is unique among long-term capacity expansion models for its high spatial resolution and statistical treatment of the impact of variable renewable generation on capacity planning and dispatch. These unique traits are extended to new Canadian regions. We present example scenario results using the fully integrated Canada-U.S. version of ReEDS to demonstrate model capabilities. The newly developed, integrated Canada-U.S. ReEDS model can be used to analyze the dynamics of electricity transfers and other grid services between the two countries under different scenarios.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2014

Representation of Solar Capacity Value in the ReEDS Capacity Expansion Model

An important issue for electricity system operators is the estimation of renewables' capacity contributions to reliably meeting system demand, or their capacity value. While the capacity value of thermal generation can be estimated easily, assessment of wind and solar requires a more nuanced approach due to the resource variability. Reliability-based methods, particularly assessment of the Effective Load-Carrying Capacity, are considered to be the most robust and widely-accepted techniques for addressing this resource variability. This report compares estimates of solar PV capacity value by the Regional Energy Deployment System (ReEDS) capacity expansion model against two sources. The first comparison is against values published by utilities or other entities for known electrical systems at existing solar penetration levels. The second comparison is against a time-series ELCC simulation tool for high renewable penetration scenarios in the Western Interconnection. Results from the ReEDS model are found to compare well with both comparisons, despite being resolved at a super-hourly temporal resolution. Two results are relevant for other capacity-based models that use a super-hourly resolution to model solar capacity value. First, solar capacity value should not be parameterized as a static value, but must decay with increasing penetration. This is because -- for an afternoon-peaking system -- as solar penetration increases, the system's peak net load shifts to later in the day -- when solar output is lower. Second, long-term planning models should determine system adequacy requirements in each time period in order to approximate LOLP calculations. Within the ReEDS model we resolve these issues by using a capacity value estimate that varies by time-slice. Within each time period the net load and shadow price on ReEDS's planning reserve constraint signals the relative importance of additional firm capacity.

14 SOLAR ENERGY↗

DOE OSTI2017

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↗

DOE OSTI2021

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↗

DOE OSTI2015

Genome-Wide Association Study Based on Multiple Imputation with Low-Depth Sequencing Data: Application to Biofuel Traits in Reed Canarygrass

Genotyping by sequencing allows for large-scale genetic analyses in plant species with no reference genome, but sets the challenge of sound inference in presence of uncertain genotypes. We report an imputation-based genome-wide association study (GWAS) in reed canarygrass (Phalaris arundinacea L., Phalaris caesia Nees), a cool-season grass species with potential as a biofuel crop. Our study involved two linkage populations and an association panel of 590 reed canarygrass genotypes. Plants were assayed for up to 5228 single nucleotide polymorphism markers and 35 traits. The genotypic markers were derived from lowdepth sequencing with 78% missing data on average. To soundly infer marker-trait associations, multiple imputation (MI) was used: several imputes of the marker data were generated to reflect imputation uncertainty and association tests were performed on marker effects across imputes. A total of nine significant markers were identified, three of which showed significant homology with the Brachypodium dystachion genome. Because no physical map of the reed canarygrass genome was available, imputation was conducted using classification trees. In general, MI showed good consistency with the complete-case analysis and adequate control over imputation uncertainty. A gain in significance of marker effects was achieved through MI, but only for rare cases when missing data were ,45%. In addition to providing insight into the genetic basis of important traits in reed canarygrass, this study presents one of the first applications of MI to genome-wide analyses and provides useful guidelines for conducting GWAS based on genotyping-by-sequencing data.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2016

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↗

DOE OSTI2024

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↗

DOE OSTI2021

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↗

DOE OSTI2021

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↗

DOE OSTI2018

Group Ring Ideals Related to Reed–Muller Codes

Reed–Muller codes are one of the most well-studied families of codes; however, there are till open problems regarding their structure. Recently a new ring-theoretic approach has emerged that provides a rather intuitive construction of these codes. This approach is centered around the notion of basic Reed–Muller codes. It is known that basic Reed–Muller codes ℳ{sub π}(m, k) over a prime field are powers of the radical RS of a corresponding group algebra and over a nonprime field there are no such equalities, except for trivial ones. In this paper, we consider the ideals ℜ{sub S}ℳ{sub π}(m, k) that arise while studying the inclusions of the basic codes and radical powers.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2011

Regional Energy Deployment System (ReEDS)

The Regional Energy Deployment System (ReEDS) is a deterministic optimization model of the deployment of electric power generation technologies and transmission infrastructure throughout the contiguous United States into the future. The model, developed by the National Renewable Energy Laboratory's Strategic Energy Analysis Center, is designed to analyze the critical energy issues in the electric sector, especially with respect to potential energy policies, such as clean energy and renewable energy standards or carbon restrictions. ReEDS provides a detailed treatment of electricity-generating and electrical storage technologies and specifically addresses a variety of issues related to renewable energy technologies, including accessibility and cost of transmission, regional quality of renewable resources, seasonal and diurnal generation profiles, variability of wind and solar power, and the influence of variability on the reliability of the electrical grid. ReEDS addresses these issues through a highly discretized regional structure, explicit statistical treatment of the variability in wind and solar output over time, and consideration of ancillary services' requirements and costs.

24 POWER TRANSMISSION AND DISTRIBUTION↗