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At least 1,351 records · Page 75

Net Zero Energy Model for Wastewater Treatment Plants

The primary objective of this study is to achieve net-zero energy (NZE) wastewater treatment plants (WWTPs) by utilizing energy efficiency opportunities (EEO), combined heat and power (CHP) systems, and other renewable energy (RE) sources, e.g., solar, water, and wind powers. Herein, this study discusses an innovative energy solution for WWTPs in the United States, and one of the WWTPs with a flow capacity of 1.5 million gallons per day (MGD) was selected as a case study. An optimization tool, Hybrid Optimization of Multiple Energy Resources (HOMER) software, is used in this study to find the best energy system configuration to run the system. An energy audit for one WWTP was conducted in early 2020 and the report is used to do this study. The proposed EEOs were able to reduce WWTP energy consumption by about 11%. The excess anaerobic digester gas was utilized in a CHP system to cover about 42% of the facility’s consumption. Also, 3% of the utility energy consumption can be claimed by microturbines in the aeration tanks. Another two renewable energy systems, solar photovoltaic (PV) with 29% and water turbines with 15%, contribute to covering 100% of the WWTP energy consumption and achieving an NZE WWTP.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Renewable Energy Potential Model: Hawaii Geothermal Supply Curves

This dataset extends the development of the Renewable Energy Potential (reV) model to include geothermal energy, with a specific focus on Hawaii. Provided here are the results of two scenarios that were modeled for geothermal energy in Hawaii: binary enhanced geothermal systems (EGS) at a depth of 2.5 km and hydrothermal binary systems at a depth of 1.5 km. The resource data for both scenarios were derived from Lautze and Haskins (2024) using an exponential method. The PFA probability of heat map was used as a look up table for which temperature gradient to use (Lautze and Haskins, 2024). The dataset provides geospatial and techno-economic details for evaluating geothermal energy potential. It includes spatial coordinates, estimated capacity factors, developable area, resource potential, and annual energy production metrics. Economic details such as levelized cost of electricity (LCOE), site development costs, transmission costs, and fixed-charge rates are also included. The reV model, originally developed for wind and solar energy, incorporates these variables to evaluate deployment constraints related to land use, environmental and cultural factors, and grid integration.

15 GEOTHERMAL ENERGY↗

Comprehensive techno-economic and life cycle greenhouse gases analysis of green ammonia production utilizing PV and wind energy: Jordan as a case study

Ammonia (NH 3 ) has emerged as a critical player in the global energy transition due to its potential as a low-carbon fuel. Conventional ammonia production methods, primarily through steam methane reforming, are significant contributors to global CO 2 emissions. This study investigates the potential of green ammonia production in Jordan by leveraging the country's abundant solar photovoltaic and wind energy resources. A comprehensive techno-economic and life cycle greenhouse gas analysis was conducted to compare green ammonia production with conventional grey and blue ammonia pathways. Here, the study utilized spatial mapping to assess renewable energy capacity factors across Jordan and optimized the integration of hybrid PV/wind systems with proton exchange membrane (PEM) electrolyzers. The results indicate that the levelized cost of green ammonia (LCOA) in Jordan varies between 900 USD/kg NH 3 and 2500 USD/kg NH 3 which is significantly higher than grey ammonia (similar to 360 USD/kg NH 3 ). Nevertheless, the carbon intensity of green ammonia production (between 0.1 kg CO 2eq /kg NH 3 and 0.5 kg CO 2eq /kg NH 3 ) is much lower than the grey ammonia (1.8 kg CO 2eq /kg NH 3 ). Finally, the results indicate that considering future reductions in capital costs and advancement in renewable energy systems and PEM electrolyzers as well as the ability to sell the co-product O 2 can reduce the LCOA by up to 92 % and make it competitive with grey ammonia.

Green Ammonia↗

Adaptive Computing for Scale-Up Problems

Adaptive Computing is an application-agnostic outer loop framework to strategically deploy simulations and experiments to guide decision making for scale-up analysis. Resources are allocated over successive batches, which makes the allocation adaptive to some objective such as optimization or model training. The framework enables the characterization and management of uncertainties associated with predictive models of complex systems when scale-up questions lead to significant model extrapolation. A key advancement of this framework is its integration of multi-fidelity surrogate modeling, uncertainty management, and automated orchestration of various computing and experimentation resources into a single integrated software package. This enables efficient multi-fidelity modeling across multiple computing resources by incorporating real-world constraints such as relative queue times and throughput on individual machines into the multi-fidelity sampling decision. We discuss applications of this framework to problems in the renewable energy space, including biofuels production, material synthesis, perovskite crystal growth, and building electrical loads.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Under-capacitated and over-powered? Rural austerity and asymmetrical negotiating relationships in US wind energy development

Though rural local governments are central actors in renewable energy development, local governments in the United States (US) remain systematically under-funded. This paper considers what the manifestations of austerity in local governments broadly and rural localities specifically mean for renewable energy development and for energy transitions. Drawing on a survey of 262 elected county officials with experience with wind energy in eight US states, this paper asks how local officials understand the impacts of wind development, how local governments are involved in wind energy negotiations, how the resources and expertise needed to navigate negotiations are distributed among counties, and analyze the relationship between local capacity, access to resources, and involvement in negotiations. We find that local officials express simultaneously affective and material concerns with the impacts of wind development and see negotiations with the developer as central to realizing local benefits. However, the expertise and staffing needed to negotiate with developers is less accessible to poorer or sparsely populated counties, and counties with lower overall revenues have narrower scopes of negotiation, and counties incre. Our results suggest that uneven rural capacity heightens an already asymmetrical relationship between localities and developers. In analyzing how infrastructure developments are shaped by relationships between localities and developers that are conditioned by austerity and (under)capacity, this paper contributes to and bridges scholarly discussions on rural austerity, rescaling, and renewable energy transitions. These results challenge conventional wisdoms around centralizing energy siting processes, contextualize popular and academic debates about opposition to renewable energy development, and highlight the need for rural reinvestment to realize meaningfully participatory energy developments.

Elmallah, Salma↗

Corrigendum to ‘Under-capacitated and over-powered? Rural austerity and asymmetrical negotiating relationships in US wind energy development’ [J. Rural Stud., 119 (2025) 1–14]

The authors regret that there is an incomplete sentence in the abstract of the article, and request that the portion “, and counties incre” be deleted from the abstract (found at the end of the sentence beginning with “However …”). The portion to be deleted is underlined and bolded below. The authors would like to apologise for any inconvenience caused. Current abstract: Though rural local governments are central actors in renewable energy development, local governments in the United States (US) remain systematically under-funded. This paper considers what the manifestations of austerity in local governments broadly and rural localities specifically mean for renewable energy development and for energy transitions. Drawing on a survey of 262 elected county officials with experience with wind energy in eight US states, this paper asks how local officials understand the impacts of wind development, how local governments are involved in wind energy negotiations, how the resources and expertise needed to navigate negotiations are distributed among counties, and analyze the relationship between local capacity, access to resources, and involvement in negotiations. We find that local officials express simultaneously affective and material concerns with the impacts of wind development and see negotiations with the developer as central to realizing local benefits. However, the expertise and staffing needed to negotiate with developers is less accessible to poorer or sparsely populated counties, and counties with lower overall revenues have narrower scopes of negotiation, and counties incre. Our results suggest that uneven rural capacity heightens an already asymmetrical relationship between localities and developers. In analyzing how infrastructure developments are shaped by relationships between localities and developers that are conditioned by austerity and (under)capacity, this paper contributes to and bridges scholarly discussions on rural austerity, rescaling, and renewable energy transitions. These results challenge conventional wisdoms around centralizing energy siting processes, contextualize popular and academic debates about opposition to renewable energy development, and highlight the need for rural reinvestment to realize meaningfully participatory energy developments.

Elmallah, Salma↗

Renewable energy integration and system operation challenge: control and optimization of millions of devices

The electric power infrastructure, originally designed and built on large-scale power plants, is evolving into a more resilient power generation and delivery system in which millions of smaller units of distributed energy generation resources units will be installed in sub-transmission and distribution networks. In order to control, manage and optimize the future grid, a hierarchical design is presented in this chapter which enables the distributed control on grid edge while inheriting the existing centralized control structure. This layered design of large-scale power system operation and control uses the following principle: reactive power control is treated as a primary control for voltage stability, and the real power control is primarily a grid-level control but can also be a supplementary control for voltage support in the case of insufficient reactive power control capacity. For the purpose of active control and operation at the distribution level, a recursive power network model is derived from nodal injection and branch power flow models. Based on the model, the proposed algorithms of hierarchical control, grid-edge inference and dynamic hosting allowance are developed and presented for multi-level controlled operation. And, a co-simulation architecture of integrated T&D system is presented to validate and demonstrate the feasibility and scalability of proposed algorithms.

Xu, Ying↗

rmon (Resource monitor) [SWR-24-128]

The resource monitor application provides monitoring, collection, and visualization of resource utilization in compute nodes. This package contains utilities to monitor system resource utilization (CPU, memory, disk, network). Here are the ways you can use it: -Monitor resource utilization for a compute node for a given set of resource types and process IDs. -Start a process and monitor its resource utilization. -Monitor resource utilization for a compute node asynchronously with the ability to dynamically change the resource types and process IDs being monitored. -Produce JSON reports of aggregated metrics. -Produce interactive HTML plots of the statistics.

Thom, Daniel [National Renewable Energy Laboratory↗

Energy 101: Distributed Energy Resources and Controllable Loads [Slides]

The Energy 101: Distributed Energy Resources and Storage presentation, developed for the Energy Technology Innovation Partnership Project (ETIPP), provides an overview of distributed energy resources (DERs) and energy storage. It covers fundamental concepts, technologies, considerations, case studies, and additional resources.

14 SOLAR ENERGY↗

Grid Strength Analysis for Integrating 30 GW of Offshore Wind Generation by 2030 in the U.S. Eastern Interconnection

Offshore wind is a key player in the transition to a decarbonized electric gird, and the United States has set ambitious goals of integrating 30 GW of offshore wind capacity by 2030 and 110 GW by 2050. To facilitate this integration, the National Renewable Energy Laboratory and the Pacific Northwest National Laboratory are conducting the Atlantic Offshore Wind Transmission Study to assess transmission solutions. To achieve the 110-GW target by 2050, meticulous planning for network expansion and resource allocation is essential; however, meeting the 2030 goals requires integrating offshore wind power with minimal system upgrades, thus necessitating a careful study of grid strength and stability. The study team developed the Automated System-wide Strength Evaluation Tool (ASSET) to assess system strength under various operating conditions and contingencies, focusing on the proposed integration of 30 GW of offshore wind power by 2030. In this paper, we provide a summary of key features of the ASSET software and results of the grid strength analysis for integrating 30 GW of offshore wind generation by 2030 in the U.S. Eastern Interconnection.

Automated System-wide Strength Evaluation Tool (AS↗

Clean Grid Vision: A U.S. Perspective - Executive Summary

Clean Grid Vision: A U.S. Perspective aims to present a range of possible pathways for future grid development and call attention to some common trends. It focuses on the lessons learned through NREL’s studies of the U.S. power sector that have measured the impacts of high-penetration VRE and have tested strategies for enhancing grid flexibility and reliability. As such, this report is limited in its scope and does not attempt to review or summarize all grid integration literature. While it refers to relevant external literature to provide context when needed, this report is primarily a summary of the National Renewable Energy Laboratory’s (NREL’s) research in the past 5 years on five key topics: grid planning and operation, grid reliability at the distribution level, grid reliability at the transmission level, demand-side resources, and power markets—each corresponds to a chapter in this report. The main insights of the report are presented in this executive summary.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Updated Oregon Floating Offshore Wind Cost Modeling [Slides]

The study provides heat maps showing updated estimates of the levelized cost of energy (LCOE) for floating offshore wind energy off the coast of Oregon. This project builds on a 2019 National Renewable Energy Laboratory (NREL) floating offshore wind power cost study in Oregon (Musial et al. 2019) and a recent NREL California cost analysis (Beiter et al. 2020). Floating wind power cost data, modeling methodology, and resource data are updated and LCOE is estimated through 2032 using 2019 as a reference year. Comparisons are made to the previous offshore wind energy cost studies (Musial et al. 2019; Beiter et al. 2020). The study does not prioritize specific sites or make judgments about marine spatial planning viability.

17 WIND ENERGY↗

Identification and Testing of Electric Vehicle Fast Charger Cybersecurity Mitigations

Fast-charging infrastructure for electric vehicles (EVs) is needed to enable and achieve the national goals of transitioning the vehicle fleet toward more electrification. Idaho National Laboratory, Oak Ridge National Laboratory, and the National Renewable Energy Laboratory (NREL) have jointly worked to identify, evaluate, and mitigate potential cyber-related consequences associated with fast charger systems. NREL contributed by considering cyberattack scenarios and consequences associated with integrating distributed energy resources (DERs) at fast-charging stations. The dynamic nature of fast-charger load profiles would encourage site operators to incorporate solar for energy cost reduction and energy storage for peak demand cost management at future charging facilities with multiple fast chargers at a site. These energy resources would be monitored and coordinated via a site energy management controller with data exchange between devices and local power metering infrastructure; thus, networking between devices and the design of the system becomes important in the overall cybersecurity posture. In addition, component vendors and system operators might have remote interfaces to any of these systems. It is therefore important to understand the breadth of the cyberattack surface and potential strategies to mitigate impacts. This project has focused on components and protocols expected to be found within a local charging site that includes multiple chargers and DER resources. Our methods and results are summarized in this final report.

42 ENGINEERING↗

Grid Strength Analysis for Integrating 30 GW of Offshore Wind Generation by 2030 in the U.S. Eastern Interconnection: Preprint

Offshore wind is a key player in the transition to a decarbonized electric gird, and the United States has set ambitious goals of integrating 30 GW of offshore wind capacity by 2030 and 110 GW by 2050. To facilitate this integration, the National Renewable Energy Laboratory and the Pacific Northwest National Laboratory are conducting the Atlantic Offshore Wind Transmission Study to assess transmission solutions. To achieve the 110-GW target by 2050, meticulous planning for network expansion and resource allocation is essential; however, meeting the 2030 goals requires integrating offshore wind power with minimal system upgrades, thus necessitating a careful study of grid strength and stability. The study team developed the Grid Strength Analysis Tool (GSAT) to assess system strength under various operating conditions and contingencies, focusing on the proposed integration of 30 GW of offshore wind power by 2030. In this paper, we provide a summary of key features of the GSAT software and results of the grid strength analysis for integrating 30 GW of offshore wind generation by 2030 in the U.S. Eastern Interconnection.

Automated System-wide Strength Evaluation Tool (AS↗

Adaptive Computing and Multi-Fidelity Strategies for Control, Design and Scale-Up of Renewable Energy Applications

We describe our ongoing research in adaptive computing and multi-fidelity modeling strategies. Our goal is to use a combination of low- and high-fidelity simulation models to enable computationally efficient optimization and uncertainty quantification. We develop optimization formulations that take into account the compute resources currently available, which act as a constraint with regards to the fidelity level simulation we can run while maximizing information gain. These strategies are being implemented into a software framework with a generalized API allowing its application to a broad range of applications, from power grid stability and buildings control to material synthesis and biofuels processing. We will discuss a few examples from these applications that can benefit from this approach, especially when considering challenges arising in scaling up experiments and simulations.

adaptive computing↗

Advancing Geothermal Research: Fiscal Year 2025 Accomplishments Report

This is a summary of geothermal work done at the National Renewable Energy Laboratory (NREL) in Fiscal Year 2025. This year brought increased attention to the geothermal industry and NREL's geothermal research portfolio. With more than 70 active projects, NREL research spanned the areas of resource exploration and characterization; conventional and next-generation geothermal technologies; subsurface thermal energy storage; heating and cooling; co-production of geothermal with critical minerals and oil and gas; modeling and analysis leveraging expertise in data science and machine learning; and more.

15 GEOTHERMAL ENERGY↗