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Modeling Needs to Support the Reconstruction Strategy of Ukraine

Ukraine has been facing difficult times. Russia started a full-scale invasion on February 24, 2022, and has caused huge human and infrastructure losses. As a result of the invasion, more than 8 million people left their homes. The Russian army has targeted Ukrainian energy sources, destroying or damaging over 50% of thermal power generation capacity (coal and gas), 30% of solar generation, and 90% of wind generation. The Russians are also threatening Ukrainian energy security, as they currently control the Zaporizhzhia nuclear power plant – Europe’s largest. In addition, Russia has destroyed 121,000 buildings, including 5,300 multistory buildings - more buildings than Ukraine built during the past five years. The occupiers destroyed or damaged 343 district heat boiler stations (destroyed 12 / damaged 331) and 8 CHPs (destroyed 4/ damaged 4). There is no doubt that Ukraine will be able to protect its sovereignty and restore its territorial integrity; however, this will be a long process. The Government of Ukraine needs to simultaneously focus on many issues, from waging war to the restoration of electricity, water, and heat supply in the territories close to the front line. In addition to these time-sensitive issues, the government also needs to plan a long term multi-sector strategy for the reconstruction of Ukraine’s economy. Ukraine initiated a broad-based political process for recovery at the International Ukraine Recovery Conference (URC 2022) in Lugano, Switzerland. Prior to URC 2022, Ukraine applied for EU membership on February 28 and was granted the status of candidate country by the European Council on June 23, 2022. More than 40 nations are fully committed to supporting Ukraine throughout its path from early to long-term recovery. In addition, these countries link a successful recovery to Ukraine’s European future (URC, 2022a). The reconstruction process will be long. The government also recognizes that it is not enough to build energy infrastructure back – it should be built back better. The government is committed to building a more sustainable and cleaner energy sector. Energy modeling can provide important insights into paths to decarbonize Ukraine’s economy while rebuilding it after the war. Pacific Northwest National Laboratory (PNNL) and the Institute for Economics and Forecasting of the National Academy of Sciences of Ukraine (IEF) work on modeling decarbonization scenarios in the energy sector of Ukraine. The teams focus on the heat sector, which includes district heat, autonomous and individual heating, and energy consumption by final energy consumption sectors, including buildings. Since the teams use world-class integrated assessment models, other sectors will be analyzed as well. The purpose of the document is to describe the needs of key Ukrainian ministries in modeling the reconstruction process. The scope of this document is limited to modeling energy consumption by the power and heat sectors, final energy consumption by buildings, and GHG emissions from these two sectors. The rest of this policy memo is organized as follows. After this introduction, Chapter 2 discusses key provisions of the reconstruction strategy with a focus on energy, buildings, heat supply, environment, and European integration aspirations. Section 3 provides an overview of recent developments and key decisions of the Government of Ukraine in the area of energy efficiency and decarbonization. Finally, Section 4 provides key suggestions on how PNNL and IEF can help the Government of Ukraine in developing strategic documents.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Reservoir Characterization and Techno-Economic Analysis of Enhanced Geothermal and Closed-Loop Systems in the Wattenberg Field of the Denver-Julesburg Basin, Colorado

This report provides details of reservoir characterization and techno-economic analysis for enhanced geothermal systems and closed-loop geothermal systems in the Denver-Julesburg Basin Wattenberg area. The analysis contributes to the Geothermal Limitless Approach to Drilling Efficiencies (GLADE) project, a multi-institutional research initiative focused on advancing geothermal energy development by reducing drilling costs and improving the rate of penetration. The GLADE project brings together national laboratories, academic institutions, and industry partners, including the U.S. Department of Energy's Geothermal Technologies Office, Occidental Petroleum, the National Laboratory of the Rockies (NLR), Los Alamos National Laboratory, Colorado School of Mines, Louisiana State University, Texas A&M University, and several drilling technology companies. As part of this effort, NLR developed and applied slender-body theory modeling tools and the GEOPHIRES simulator to support techno-economic analysis. The slender-body theory wellbore simulator evaluated thermal performance in U-loop, Eavor-type multilateral, and enhanced geothermal system well configurations. Results indicated that an optimized single U-loop design delivers an outlet temperature of 168.8 degrees Celsius,stabilizing at a final outlet temperature of 135.3 degrees Celsius. Heat production also improved significantly, with an average thermal output of 16.9 MWth and a final thermal output of 11.0 MWth. These results provided critical baseline data for selecting optimized systems for techno-economic analysis. Building on these outputs, NLR applied the GEOPHIRES techno-economic simulator to estimate the levelized cost of electricity for both the Eavor multilateral and enhanced geothermal systems. The sensitivity analysis showed that drilling costs exert a particularly strong impact on the levelized cost of electricity of multilateral systems. Therefore, advances in drilling technology and improved drilling rates could yield significant gains in the economic performance of these systems. In this context, the GLADE project directly supports the U.S. Department of Energy's mission to reduce the cost of geothermal energy and accelerate the deployment of next-generation geothermal technologies.

15 GEOTHERMAL ENERGY↗

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↗

Viable Economic Frameworks and Regulatory Barriers for Community Microgrids

Community microgrids – microgrids with more than one piece of customer- and utility-owned distribution equipment contained in the isolation boundary – are an option for providing resilience to meet targeted community and utility needs. Because multiple investors, including customers, are involved there is a lack of clarity around viable ownership models, roles and responsibilities, and compensation mechanisms. Together, these aspects describe an economic framework. To be viable, an economic framework not only needs to provide the possibility of all parties agreeing to the microgrid but also needs to meet regulatory guidelines. This report contains learnings from present-day community microgrid tariffs and programs, regulatory filings, and experiences shared within an interest group to highlight regulatory barriers to community microgrids and identify several viable economic frameworks for community microgrids.

24 POWER TRANSMISSION AND DISTRIBUTION↗

High-Temperature Heat Pump Model Documentation and Case Studies

High temperature heat pumps (HTHPs) have the potential to serve two valuable functions in the U.S. industry. First, by valorizing and elevating waste heat streams, HTHPs can improve industrial energy efficiency. Second, by electrifying process heat generation, HTHPs can replace combustion technologies with less carbon-intensive sources of energy and reduce industrial greenhouse gas emissions. In certain applications, the combination of increased efficiency, cost savings, and emissions reduction makes HTHPs a promising component of strategies for industrial electrification and clean energy transition. Researchers at NREL have developed a HTHP model. This model has both a physics-based performance estimation component and an economic evaluation component designed to demonstrate the potential economic competitiveness of HTHPs. This document has three main sections. First, an overview of HTHPs is provided as a literature review of relevant information to provide the reader with state-of-the-art information. Second, a description of the HTHP model is provided along with detailed instructions about how to use the model. Third, case studies are provided to showcase the deployment of the HTHP model.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Evaluation of Mechanistic and Empirical Models against Existing FFRD and LOCA Experimental Databases

The desire of the nuclear industry to improve the economics of existing nuclear power plants has necessitated research into the potential of a phenomenon known as fuel fragmentation, relocation, and dispersal (FFRD). This phenomenon is possible during a loss-of-coolant accident (LOCA) at relatively high burnup. The Nuclear Energy Advanced Modeling and Simulation program has been developing simulation capabilities for FFRD and LOCA in the BISON fuel performance code for multiple years. This year, the effort has been focused on evaluating new lower length scale informed pulverization thresholds as well as updating and adding new empirical models for various phenomena. Models added or updated this year include a preliminary transient fission gas release model, new high-temperature Zircaloy creep models, a Zircaloy rupture opening area model, and a temperature-dependent emissivity during radiation from the fuel rod to the surrounding atmosphere. The models are verified through implementation tests to demonstrate code correctness after addition to BISON. The models are then assessed against a subset of the existing BISON validation suite for LOCA and FFRD cases. Two new cases, Studsvik Rods 192 and 193, have been added. The results indicate that the inclusion of a bubble pressure evolution model in the bubbles in the high-burnup structure has the largest impact compared to the 3D fracture criterion on reducing the calculated amount of pulverized fuel.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Switchgrass ( Panicum Virgatum ) and Miscanthus ( Miscanthus × Giganteus ) Long-Term Yield Patterns Reveal Consistent Productivity Declines

Perennial grasses like switchgrass ( Panicum virgatum ) and miscanthus ( Miscanthus × giganteus ) are expected to supply a substantial amount of the United States bioeconomy's feedstock demand. However, uncertainties around their long-term yields challenge the viability of their potential and limit their wider adoption. To resolve their long-term yield patterns, we analyzed over 200 plantings of switchgrass and miscanthus across Michigan and Wisconsin, USA, measured over 5–15 years. We found a consistent two-phase long-term yield dynamic; during a yield-building phase , peak yields occurred within 4–5 years after planting, followed by a yield-decline phase in which switchgrass and miscanthus lost 30%–47% and 14%–40% of peak yields, respectively. Among the potential drivers of this dynamic and the yield decline, we found that weather conditions had little impact, as the variation across years was not large enough to drive the observed yield differences. Added nitrogen increased peak yields by 10%–20% and attenuated the yield decline by 20%–50%. However, since fertilized stands still showed a yield decline, other factors became limiting as stands aged. This conserved long-term yield dynamic has direct implications on management. A farm-to-gate economic analysis suggests replanting switchgrass and miscanthus 5 and 9 years following their peak yields maximizes profit over a 30-year time horizon. Results call for further management and breeding strategies to mitigate the yield-decline phase, and for reparameterization of global bioenergy models with carbon capture and storage, which may overestimate yields and the economic and environmental benefits of crops grown for bioenergy feedstocks.

bioenergy↗

Informing climate adaptation strategies using ecological simulation models and spatial decision support tools

Introduction: Forest landscapes offer resources and ecosystem services that are vital to the social, economic, and cultural well-being of human communities, but managing for these provisions can require socially and ecologically relevant trade-offs. We designed a spatial decision support model to reveal trade-offs and synergies between ecosystem services in a large eastern Cascade Mountain landscape in Washington State, USA. Methods: We used process-based forest landscape (LANDIS-II) and hydrology (DHSVM) models to compare outcomes associated with 100 years of simulated forest and wildfire dynamics for two management scenarios, Wildfire only and Wildfire + Treatments. We then examined the strength and spatial distribution of potential treatment effects and trends in a set of resources and ecosystem services over the simulation period. Results: We found that wildfire area burned increased over time, but some impacts could be mitigated by adaptation treatments. Treatment benefits were not limited to treated areas. Interestingly, we observed neighborhood benefits where fire spread and severity were reduced not only in treated patches but in adjacent patches and landscapes as well, creating potential synergies among some resource benefits and services. Ordinations provided further evidence for two main kinds of outcomes. Positive ecological effects of treatments were greatest in upper elevation moist and cold forests, while positive benefits to human communities were aligned with drier, low- and mid-elevation forests closer to the wildland urban interface. Discussion: Our results contribute to improved understanding of synergies and tradeoffs linked to adaptation and restoration efforts in fire-prone forests and can be used to inform management aimed at rebuilding resilient, climate-adapted landscapes.

54 ENVIRONMENTAL SCIENCES↗

An Overview of the Waste-to-Energy System Simulation (WESyS) Model

The leveraging of waste streams for energy and chemical production could add revenue to waste disposal operations, and it presents opportunities for addressing a variety of economic and environmental objectives at the local, state, and national levels. The Waste-to-Energy System Simulation (WESyS) model is a system dynamics model that was created to simulate the development of the U.S. waste-to-energy industry over time. For each of the three primary waste resources modeled (landfills, concentrated animal feeding operations, and publicly owned treatment works), WESyS simulates technically feasible scenarios for use of the waste, including direct conversion to fuels, and anaerobic digestion followed by flaring, electricity generation, combined heat and power, cleanup and compression to compressed natural gas, and cleanup and injection into an existing pipeline. The model allows users to explore numerous plausible future scenarios for the development of the U.S. waste-to-energy industry. This report provides an overview of the WESyS model and documents the key assumptions, equations, and data sources used to create the model.

09 BIOMASS FUELS↗

Projecting Future Colorado River Basin Water and Hydropower Operations

Drought, variable renewable energy (VRE) resources (primarily wind and photovoltaic technologies), and power markets can all impact hydropower plant operations. We analyze how these three factors collectively may potentially change the future operation and economics of federal dams and hydropower plants located in the Colorado River Basin (CRB). Federal CRB energy and capacity resources, including 4,200 MW of hydropower capacity, are marketed by Western Area Power Administration (WAPA) and sold through long-term Firm Electric Service (FES) contracts to entities located in 15 western and central States that serve millions of electricity consumers. The parameters of FES contracts allow a wide range of scheduling flexibility for FES customers. The FES customers will adjust the timing of energy delivery according to the changing water, power market, and VRE contribution level to the power grid. We simulate and project water and hydropower operations with two models: 1) reservoir operation and 2) power system operation (production cost) with various temporal granularity. We consider two sets of grid scenarios (one representing today's infrastructure, and one representing higher VRE contributions in 2036) and two sets of water scenarios (drought and normal hydrology). We modeled scenarios to understand the power market-energy price levels and patterns, FES customer scheduling, hydropower economics, WAPA finances and hydropower operation for various hydrologic conditions, and VRE contribution level to the power grid. The detailed modeling framework includes: (1) creating ensembles of CRB hydrologic and hydropower futures, (2) selecting representative futures, (3) simulation of FES customer contracts, (4) simulating western U.S. power grid economic scheduling and dispatch under two VRE contribution levels, utilizing information from modeling steps (1)-(4), (5) assessment of reservoir water and hydropower operation, and (6) comparing scenario operations and economics. Our study team comprising WAPA, and an interdisciplinary team of national labs will gain insight into how WAPA can prepare for and adapt its practices in response to an evolving U.S. power grid.

Colorado River↗

Use Cases and Model Development of Thermal Storage Coupling for Advanced Nuclear Reactors

This report discusses the different options for coupling thermal energy storage (TES) systems to advanced nuclear power plants (A-NPPs) in order to enable flexible and hybrid plant operation. An advanced light-water reactor (ALWR) and a high-temperature gas-cooled reactor (HTGR) were selected as the initial use cases for demonstrating a thermally balanced energy storage coupling design for thermal power extraction. Cost functions for the A-LWR were derived from the fully balanced models that were developed based on three different coupling options with three different thermal energy bypass ratios. For the next steps, cost functions for the HTGR will also be derived, and additional nuclear reactors (e.g., a liquid-cooled fast reactor [LFR] or molten-salt reactor [MSR]) will be evaluated for coupling with TES in similar fashion, including the evaluation of their steady-state condition models and cost functions. The models presented herein showcase several design considerations, focusing on optimal deployment methodologies for achieving steady-state operation with minimum disruption to the nuclear power generation cycle. This report presents the results of steady state models developed using Aspen HYSYS®, wherein the thermal energy bypass for an NPP-TES coupling was varied up to 50%. The various components were sized using Aspen Process Economic Analyzer (APEA) and Aspen Exchanger Design and Rating (EDR), when applicable. Cost functions from these models were developed using the latest publicly available data obtained from APEA V11. The current steady-state models and cost functions provide a baseline for additional work focusing on dynamic operation and process optimization by using Idaho National Laboratory (INL)’s Framework for Optimization of Resources and Economics (FORCE) tools to evaluate the technoeconomic viability and transient operations of TES-coupled A-NPPs.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Profitability, Scalability and Optimized Siting for Waste-to-Energy Supply Chains: A Case Study on Hydrothermal Liquefaction

Waste-to-Energy (WtE) conversion technologies have the potential to simultaneously reduce waste volumes, treatment-related emissions, and carbon intensity while producing valuable energy services. However, questions remain regarding under which conditions emerging WtE technologies are feasible to deploy. In this project, we develop an optimized siting method for WtE technologies to assess cost-effective WtE processor locations, throughput scales, and profitability. We apply the model using Hydrothermal Liquefaction (HTL) as an example WtE technology. We develop calibrated capital and operating expense cost curves based on literature data to study the techno-economic characteristics of WtE supply chains. Prior to solving the siting optimization, we analyze the model parameters to describe organic waste management system behavior under four different HTL deployment configurations: Co-Processing, where HTL plants send biocrude to existing conventional refineries via assumed pipelines; Co-Location, where biorefineries are co-located with HTL plants; and two alternative Standalone Biorefining cases, where distributed HTL plants transport biocrude intermediate via either assumed pipelines or trucking to centralized biorefineries. We also define and apply several feedstock gate fee calculations, representing different revenue distribution options, to investigate how bioproduct value could impact WtE supply chain economics in terms of waste producer and processor profit or cost reduction.

09 BIOMASS FUELS↗

GCAM Base Year Update

In FY21 we worked to update the Global Change Analysis Model (GCAM) to match historical energy consumption and technology cost trends and near-term economic growth expectations using available historical data out to 2019. We have done this in a way that builds the capacity to more easily update the model in the future to make GCAM a robust and readily updatable tool for decarbonization analysis.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Economic analysis of the benefits to petroleum refiners for low carbon boosted spark ignition biofuels

A refinery modeling framework is developed to estimate the benefits of blending high-quality biofuels directly with refinery gasoline components for attaining a premium grade fuel (also termed as Co-Optima Boosted SI gasoline here). Our results change the paradigm of bio-blendstocks (BBs) being competitors to fossil components, by identifying opportunities for refineries to add value to their product slate, from some favorable BB properties. This potential value can be characterized by calculating the breakeven value (BEV), as defined down below. The proposed modeling framework incorporates extensive data from (1) projected product over the next few decades, (2) crude oil and refinery products pricing, and (3) fuel specifications. The complete refinery models serve as a basis for assessing the value of biofuels, assuming profitability remains the same for representative petroleum refinery configurations. Our assessment showed wide range of variation of biofuels BEV from $\$$20-$\$$120/bbl, within the considered blending level and crude prices. Further, the BEV was correlated with the fuel octane ratings such as octane numbers (research, RON and motor octane numbers, MON) and both antiknock index (AKI, average of RON and MON) and sensitivity (S, difference between RON and MON), with a slightly higher correlation with the sensitivity. However, the expected decrease in gasoline demand for the upcoming years could negatively impact biofuels demand and value, in a business-as-usual scenario. Our analysis also showed a more valuable bio-blendstocks incorporation in smaller refineries since they can enhance the capabilities for producing specialty, high-value fuels/products, and introduce high octane-barrels into otherwise constrained blending operations. Additional implications towards refiners include opportunities to rebalance operations, access to high-value fuel markets, and synchronization with broader transportation industry trends. Furthermore, results indicate the value of Co-Optima boosted spark ignition (BSI) efficiency gains can extend to refiners to incentivize decarbonization and diversified feedstock production.

09 BIOMASS FUELS↗

Modular Integrated System for Carbon-Neutral Methanol Synthesis Using Direct Air Capture and Carbon-Free Hydrogen Production

This study investigates the development and economic analysis of a modular integrated system for carbon-neutral methanol synthesis, leveraging direct air capture (DAC) and solid oxide electrolysis cells (SOEC) for carbon dioxide and hydrogen production, respectively. The proposed system integrates a novel building-based DAC process, functionalized solid sorbents, and low-energy SOEC technology, aiming to minimize operational and capital costs. A comparison between the base case system (1,000 t methanol/year) and a scaled-up model (14,758 t methanol/year) reveals significant improvements in efficiency and economic feasibility. The scaled-up system achieves a levelized cost of methanol (LCOM) of $740/t, a 7.5% reduction compared to that of conventional DAC-based systems, while utilizing existing building HVAC infrastructure for air handling. Detailed sensitivity analyses were conducted, evaluating the effects of plant capacity and air flow rate on the LCOM, demonstrating the scalability of the building-based DAC system. The cradle-to-gate life cycle analysis shows that the proposed process using renewable-sourced electricity achieves a 38% reduction in greenhouse gas (GHG) emission compared to reported values of green methanol production technologies that use a conventional DAC and a conventional methanol synthesis catalyst. When fossil-sourced electricity is used in the proposed process, it leads to about a 37.5% reduction in GHG emission in comparison to reported values for conventional methanol production technologies using steam methane reforming technology and fossil-sourced electricity.

alcohols↗

Reduce Revenue Versus Increase Expenditure: Fires and Plant Invasion Drive Soil Carbon Loss With Different Mechanisms in a Mediterranean Shrubland

Fires and plant invasions threaten Mediterranean ecosystems substantially, particularly in the context of changing climate. Our study utilized a data-model integration approach to assess the response of soil organic carbon (SOC) to fires and plant invasion under three Shared Socio-Economic Pathway (SSP) scenarios (SSP1-26, SSP2-45, and SSP5-85). We parameterized the CLM-Microbe model and then investigated the individual and interactive impacts of fires and plant invasion on soil C by comparing factorial simulations of initialization (fire/no wildfire in 2021), fire module on/off, and with and without plant invasion during 2023–2100 in a Mediterranean ecosystem. The simulations indicated a marked C loss due to the 2021 wildfire, projected fires, and plant invasion across all future climate scenarios. Specifically, the 2021 wildfire, projected fires, and plant invasion reduced the SOC (0–30 cm) by 0.12, 0.26, and 0.15 kg C m −2 under SSP1-26, 0.12, 0.30, and 0.12 kg C m −2 under SSP2-45, and 0.12, 0.24, and 0.13 kg C m −2 under SSP5-85, respectively. However, fires and plant invasion decreased SOC through distinct mechanisms. The effects of the 2021 wildfire occurred due to its negative legacy on soil microbial community and, thus, litter accumulation, suppressing the formation of soil carbon via decomposition. Influences of projected fires happen via consuming fuel and suppressing carbon input to soils. In contrast, the impacts of plant invasions were due to enhanced microbial respiration, leading to C loss. In conclusion, these findings emphasize the need for tailored C sequestration strategies considering the disparate effects of fires and plant invasions in the Mediterranean climate.

microbe↗

Novel reusable animal model for comparative evaluation of in vivo growth and protein-expression of Escherichia coli O157 strains in the bovine rumen

Previously, we had demonstrated that Escherichia coli O157:H7 (O157) strain 86–24 expresses proteins involved in survival rather than virulence in vitro in rumen fluid from dairy cattle limit fed a maintenance diet. Here, we verified if this observation would be true for different O157 strains grown in vitro in rumen fluid from, and in vivo in the rumen of, animals on contrasting maintenance (high fiber) and lactation (high energy-protein) diets usually limit fed to dairy cattle. For the in vivo studies, an economical, novel, reusable and non-terminal rumen-fistulated animal model permitting simultaneous evaluation of multiple bacterial strains in the bovine rumen was developed. All experiments were conducted in duplicate using different animals to account for host-related variations. The O157 strains included, 86–24, EDL933 and the super shed SS-17. E. coli Nal R (#5735), derived from a bovine intestinal commensal E. coli, was included as a control. As expected, diet influenced ruminal pH and volatile fatty acid (VFA) composition. The pH ranged from 6.2–7.0 and total VFA concentrations from 109–141 μM/ml, in animals fed the maintenance diet. In comparison, animals fed the lactation diet had a ruminal pH ranging between 5.18–6.0, and total VFA of 125–219 μM/ml. Strain dependent differences in O157 recovery from the rumen fluid of cattle fed either diet was observed, both in vitro and in vivo, with O157 strains 86–24 and EDL933 demonstrating similar survival patterns. Analysis of the O157 proteomes expressed in the rumen fluid/rumen verified previous observations of adaptive responses. Any difference in the adaptive response was mainly influenced by the animal’s diet and growth conditions (in vitro and in vivo) and not the O157 strain. These new insights into the O157 responses could help formulate modalities to control O157 across strains in cattle at all stages of husbandry.

59 BASIC BIOLOGICAL SCIENCES↗

Forecasting Distributed PV Adoption in Barranquilla, Colombia [Slides]

The objective of the dGen Colombia project is to provide projections to 2050 on distributed PV deployment by sector for a range of scenarios for Barranquilla, Colombia. NREL used the open-source Distributed Generation Market Demand Model (dGen) adapted for international projects for this analysis. As part of this analysis, technical potential, economic potential, and adoption projections of rooftop and groundmount PV for the city of Barranquilla are presented. Five main scenarios and their combinations were modeled to provide insight on the impact of increased demand from electric vehicles, air conditioning, and time-of-use tariffs.

14 SOLAR ENERGY↗