SEARCH · Engineering Papers

Results for “Renewables”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 163 records · Page 9

All sources NASA NTRS DOE OSTI

DOE OSTI2023

Distributed Embedded Energy Converter Technologies for Marine Renewable Energy (A Technical Report)

The domain of distributed embedded energy converter technologies (DEEC-Tec) is a nascent and underexplored paradigm for harvesting and converting marine renewable energy. The paradigm distinguishes itself through its use of many small distributed embedded energy converters (DEECs) that, ultimately, are assembled through the creation of "DEEC-Tec metamaterials" to create an overall larger marine renewable energy harvesting and converting structure. As an example, such a structure could be an ocean wave energy converter - a converter whose structure is made from various types of DEEC-Tec metamaterials that harvests ocean wave energy and converts that energy into something more useful such as electricity. To that end, DEEC-Tec can be viewed at three different technology levels: (1) individual distributed embedded energy converters, also known as DEECs; (2) DEEC-Tec metamaterials-essentially, pseudo-materials made from the interconnection of many DEECs; and (3) overall larger complete marine renewable energy harvesting-converting structures-these structures being made from DEEC-Tec metamaterials. Arising directly from the application of DEEC-Tec to harvest and convert ocean wave energy are several noteworthy benefits, some of which include: (1) the lack of load concentrations into singular components or subsystems, (2) broad-banded ocean wave energy frequency harvesting and conversion, and (3) inherent redundancy-failure of some individual DEECs does not represent a failure of an entire DEEC-Tec-based WEC. This report describes DEEC-Tec by way of descriptions of those three technology levels: individual DEECs, DEEC-Tec metamaterials, and DEEC-Tec-based WECs. Moreover, the report describes corresponding research approaches and methodologies for related concepts such as DEEC-Tec-based WEC topologies and morphologies in addition to manufacturing and fabrication techniques found suitable for the application of DEEC-Tec within the general domain of marine renewable energy-moving beyond only ocean wave energy conversion.

16 TIDAL AND WAVE POWER↗

DOE OSTI2023

Electric Vehicle Charging Management in Smart Energy Communities to Increase Renewable Energy Hosting Capacity

Abnormal climates due to global warming have emerged as a big concern in the global community. To mitigate climate change and achieve sustainability, distributed energy resources (DERs), including solar and wind, have been recently deployed in power systems. As the penetration level of DERs has increased, however, it caused a multitude of issues in the power systems, such as voltage fluctuation in the distribution network limiting renewable hosting capacity. On the other hand, the electric vehicle (EV) industry is rapidly growing to facilitate the transition to a carbon-neutral community, illuminating the potential of EVs as a flexible grid asset to mitigate some of the issues and improve grid operation, if properly exploited. To explore the potential of EVs, this paper proposes an EV scheduling strategy. By using an optimal EV charging scheduling proposed, distribution system operators (DSOs) can minimize their operating costs and stably operate the system with a high level of DERs. To validate the method, a modified IEEE 33-bus system with DERs is developed. The case study shows the proposed scheduling strategizes EV charging to reduce the cost of PV curtailment. In the study, the method outperforms the renewable-only case with curtailment by 4.97% in DSO cost. It also demonstrates its potential to increase the renewable hosting capacity by harmonizing EV charging with renewables.

ADVANCED PROPULSION SYSTEMS,POWER TRANSMISSION AND↗

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 OSTI2020

Benefit Analysis of Long-Duration Energy Storage in Power Systems with High Renewable Energy Shares

The integration of high shares of variable renewable energy raises challenges for the reliability and cost-effectiveness of power systems. The value of long-duration energy storage, which helps address variability in renewable energy supply across days and seasons, is poised to grow significantly as power systems shift to larger shares of variable generation such as wind and solar. This study explores the system-level services and associated benefits of long-duration energy storage on the 2050 Western Interconnection (WI). The operation of the future WI system with 85% renewable penetration is simulated using a two-stage production cost model. The impact of long duration energy storage on systemwide operations is examined for the 2050 WI system, using a range of round-trip efficiencies corresponding to four different energy storage technologies. The analysis projects the energy storage dispatch profile, system-wide production cost savings (from both diurnal and seasonal operation), and impacts on generation mix, and change in renewable generation curtailment.

25 ENERGY STORAGE↗

DOE OSTI2023

Recent Progress in Electrochemical Upgrading of Bio-Oil Model Compounds and Bio-Oils to Renewable Fuels and Platform Chemicals

Sustainable production of renewable carbon-based fuels and chemicals remains a necessary but immense challenge in the fight against climate change. Bio-oil derived from lignocellulosic biomass requires energy-intense upgrading to produce usable fuels or chemicals. Traditional upgrading methods such as hydrodeoxygenation (HDO) require high temperatures (200–400 °C) and 200 bar of external hydrogen. Electrochemical hydrogenation (ECH), on the other hand, operates at low temperatures (<80 °C), ambient pressure, and does not require an external hydrogen source. These environmental and economically favorable conditions make ECH a promising alternative to conventional thermochemical upgrading processes. ECH combines renewable electricity with biomass conversion and harnesses intermediately generated electricity to produce drop-in biofuels. This review aims to summarize recent studies on bio-oil upgrading using ECH focusing on the development of novel catalytic materials and factors impacting ECH efficiency and products. Here, electrode design, reaction temperature, applied overpotential, and electrolytes are analyzed for their impacts on overall ECH performance. We find that through careful reaction optimization and electrode design, ECH reactions can be tailored to be efficient and selective for the production of renewable fuels and chemicals. Preliminary economic and environmental assessments have shown that ECH can be viable alternative to convention upgrading technologies with the potential to reduce CO2 emissions by 3 times compared to thermochemical upgrading. While the field of electrochemical upgrading of bio-oil has additional challenges before commercialization, this review finds ECH a promising avenue to produce renewable carbon-based drop-in biofuels. Finally, based on the analyses presented in this review, directions for future research areas and optimization are suggested.

09 BIOMASS FUELS↗

DOE OSTI2020

Dynamic Optimal Dispatch of Energy Systems with Intermittent Renewables and Damage Model

With the increasing penetration of intermittent renewable energy sources into the grid, there is a growing need for process systems-based strategies that integrate dispatchable and variable energy systems for supplying the demand while maintaining grid reliability. The proposed framework corresponds to a dynamic mixed-integer linear programming optimization approach that integrates coal-fired and natural gas-fired power plants, NaS batteries for energy storage, and solar/wind energy to supply the demand. This optimization approach considers an economic goal and constraints to provide power balance while maintaining the overall damage of the natural gas combined cycle (NGCC) power plant drum under a maximum stress as well as avoiding the overheating of the NGCC superheater and reheater. Renewable curtailment levels are also retained at minimum levels. Case studies are analyzed considering different loads and renewable penetration levels. The results show that the demand was met for all cases. Grid flexibility was mostly provided by the NGCC, while the batteries were used sparingly. In addition, considering a CO 2 equivalent analysis, the environmental performance was intrinsically connected to grid flexibility and the level of renewable penetration. Stress analysis results reinforced the necessity for an equipment health-related constraint.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Learning from Arctic Microgrids: Cost and Resiliency Projections for Renewable Energy Expansion with Hydrogen and Battery Storage

Electricity in rural Alaska is provided by more than 200 standalone microgrid systems powered predominantly by diesel generators. Incorporating renewable energy generation and storage to these systems can reduce their reliance on costly imported fuel and improve sustainability; however, uncertainty remains about optimal grid architectures to minimize cost, including how and when to incorporate long-duration energy storage. This study implements a novel, multi-pronged approach to assess the techno-economic feasibility of future energy pathways in the community of Kotzebue, which has already successfully deployed solar photovoltaics, wind turbines, and battery storage systems. Using real community load, resource, and generation data, we develop a series of comparison models using the HOMER Pro software tool to evaluate microgrid architectures to meet over 90% of the annual community electricity demand with renewable generation, considering both battery and hydrogen energy storage. We find that near-term planned capacity expansions in the community could enable over 50% renewable generation and reduce the total cost of energy. Additional build-outs to reach 75% renewable generation are shown to be competitive with current costs, but further capacity expansion is not currently economical. We additionally include a cost sensitivity analysis and a storage capacity sizing assessment that suggest hydrogen storage may be economically viable if battery costs increase, but large-scale seasonal storage via hydrogen is currently unlikely to be cost-effective nor practical for the region considered. While these findings are based on data and community priorities in Kotzebue, we expect this approach to be relevant to many communities in the Arctic and Sub-Arctic regions working to improve energy reliability, sustainability, and security.

25 ENERGY STORAGE↗

NASA NTRS2014

High Resolution Mapping of Soils and Landforms for the Desert Renewable Energy Conservation Plan (DRECP)

The Desert Renewable Energy Conservation Plan (DRECP), a major component of California's renewable energy planning efforts, is intended to provide effective protection and conservation of desert ecosystems, while allowing for the sensible development of renewable energy projects. This NASA mapping report was developed to support the DRECP and the Bureau of Land Management (BLM). We outline in this document remote sensing image processing methods to deliver new maps of biological soils crusts, sand dune movements, desert pavements, and sub-surface water sources across the DRECP area. We focused data processing first on the largely unmapped areas most likely to be used for energy developments, such as those within Renewable Energy Study Areas (RESA) and Solar Energy Zones (SEZs). We used imagery (multispectral and radar) mainly from the years 2009-2011.

Mapping↗

DOE OSTI2020

Innovations in Renewable Energy Technologies, Systems, and Energy Analysis

Costs for renewable energy technologies have declined rapidly in the past decade and their use for residential, commercial, and utility scale electricity has therefore grown exponentially. As the energy mix diversifies, energy analysis becomes increasing important, requiring renewable energy to integrate with other reduced emission energy sources, such as small modular nuclear reactors and carbon capture and utilization. Energy analysis can also explore the expansion of clean energy into new sectors, such as industrial processes and electrification. The U.S. National Renewable Energy Laboratory (NREL) and the Joint Institute for Strategic Energy Analysis (JISEA), which is a partnership of NREL and universities, study the integration and application of clean energy technologies into existing and new sectors. This presentation includes an overview of NREL and JISEA and summarizes innovations in renewable energy technologies and energy systems analysis.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2020

Integrating Renewable Energy into Mining Operations

The mining industry is a major source of raw materials for several industries such as manufacturing, transportation, construction, energy, and mining industry itself. It is anticipated that demand for raw materials is going to increase as the population growth and many low-income economies shift to middle-income countries. The increase in mineral demand accompanies by falling mineral ore grade is expected to increase energy demand raising concern of greenhouse gas emission (GHG). Renewable energy can provide mine operators with solutions to several of the challenges they face today, including energy costs, fossil fuel volatility, social license to operate, and meeting environmental, societal, and governance goals. However, the integration of wind, solar, storage, and other renewable technologies face several barriers that are generally not well understood. Many of these barriers will require further research, development, demonstration, and deployment before we see higher levels of renewables adoption in the mining industry. Thus, this report highlights renewable opportunities, barriers, and enabling approaches.

clean energy↗

DOE OSTI2020

Integrating Renewable Energy in the Iron and Steel Industry: Challenges, Opportunities, and Enabling Approaches

Renewable energy can help mine operators with several challenges they face today, including energy costs, fossil fuel volatility, social license to operate, and meeting environmental, societal, and governance goals. However, the integration of wind, solar, storage, and other renewable technologies face several barriers that are generally not well understood. Many of these barriers will require further research, development, demonstration, and deployment before we see higher levels of renewables adoption in the mining industry. Thus, this poster highlights renewable opportunities, barriers, and enabling approaches.

energy demands↗

DOE OSTI2021

Opportunities and Challenges for Nuclear-Renewable Hybrid Energy Systems

Nuclear-renewable hybrid energy systems (also known as integrated nuclear-renewable systems) are conceptual systems that have two or more energy inputs and produce two or more products. They maximize profitability, and usually equipment utilization, by adjusting between the products depending upon the availability of resources and market value. For example a nuclear-renewable hybrid energy system that produces electricity and hydrogen would maximize sales of electricity when its price is high and shift to hydrogen production when the electricity price is low. This presentation summarizes the results of several economic analyses of nuclear-renewable hybrid energy systems and they key overall conclusions from those analyses.

ENERGY PLANNING, POLICY, AND ECONOMY,ENVIRONMENTAL↗

DOE OSTI2021

Opportunities and Challenges for Nuclear-Renewable Hybrid Energy Systems

economic analysis↗

DOE OSTI2022

Highlights of Two Case Studies Illustrate the Diverse Renewable Energy Opportunities for Colorado Agriculture

This presentation highlights the findings from two renewable energy case studies conducted by the Joint Institute for Strategic Energy Analysis (JISEA) for the Colorado Department of Agriculture and the Colorado Energy Office in 2021. The case studies; one exploring renewable energy integration for greenhouses and one evaluating biogas production potential for a dairy, illustrate the wide variety of renewable energy opportunities and the significant potential benefits of renewable energy in the agriculture sector in Colorado.

agriculture↗

DOE OSTI2022

Intersections of Disadvantaged Communities and Renewable Energy Potential: Analyses to Inform Equitable Investment Prioritization

Renewable energy development can bolster local economies through job creation, local tax revenues, and reduced energy costs; however, communities most in need of economic development and employment opportunities often see lower levels of renewable energy deployment. We sought to identify areas where indicators of disadvantaged communities intersect with high generation potential from cost- effective renewable energy opportunities. This presentation highlights the geospatial intersection of the technical potential and levelized cost of energy for three renewable technologies (residential solar, utility solar, and land-based wind) and three sociodemographic metrics (energy burden, unemployment, and employment in mining, quarrying, and oil and gas extraction). This research and the associated county-level data set are intended to inform national- and state-level energy-related assistance programs, economic development efforts, and infrastructure programs seeking to prioritize investments in disadvantaged communities.

disadvantaged communities↗

DOE OSTI2023

Spatiotemporal Super-Resolution with Generative Machine Learning for Creating Renewable Energy Resource Data Under Climate Change Scenarios

As we plan for a future with higher penetrations of renewables and increasing electrification, it becomes more important to understand how the electricity grid will operate under a variety of weather events. We must also consider that the weather our future grid will experience will be different and possibly more extreme than the historical weather that we have extensive data for. We can use data from global climate models (GCMs) to help understand how our climate may change over the next several decades, but there is often a significant gap between the low-resolution GCM data and the high-resolution weather data required to study power systems under specific weather events. Therefore, our objective in this work is to develop tools that can bridge this gap by using low-resolution GCM data to create realistic high-resolution weather datasets that can be used to study renewable energy generation and electricity demand. To accomplish this objective, we have developed a set of generative machine learning models that can rapidly downscale GCM daily average output data at an approximate grid resolution of 100km to hourly data at an approximate 4 km grid resolution. The models can be used to create high resolution data from nearly any GCM included in the Coupled Model Intercomparison Project (CMIP) Phase 5 or 6. Our methods include all datasets regularly used to study the integration of wind and solar power plants as well as changes in electricity demand due to heating and cooling loads. These models and datasets enable power systems modelers to study climate change-influenced weather events and their impact on the grid. We have downscaled and validated wind, solar, temperature, and humidity data with very promising results. The generative machine learning methods are computationally efficient and produce data that has similar statistical characteristics to current state-of-the-art historical datasets. We have trained initial generative models and produced an initial dataset collectively referred to as Sup3rCC: Super-Resolved Renewable Energy Resource Data with Climate Change Impacts. The data covers a (mostly) historical period from 2015-2025 and a future period from 2050-2059. We have also taken hypothetical high-electrification load data and scaled the heating and cooling loads with respect to the 2050-2059 high-resolution Sup3rCC meteorology. The results show how future levels of renewable energy generation and electrified load may be impacted by climate change, setting the stage for capacity expansion models to consider a dynamic climate through model years.

climate change↗

DOE OSTI2023

Identifying Potential Candidates for Renewable Energy Zones (REZs) in Bangladesh

Bangladesh faces several hurdles to achieving its renewable energy objectives, such as land availability and transmission congestion. Renewable Energy Zones (REZ), which are geographic areas with high-quality utility-scale renewable resources, suitable land topography, and commercial interest, can help address these challenges and support long-term generation and transmission planning. This study focuses on solar PV (fixed-tilt) and onshore wind, leveraging recently developed high temporal and spatial resolution resource data. In the moderate land exclusion scenario, large "study areas" are identified in Bangladesh with capacity factors in the top 25% for the entire country - 5 for wind and 8 for solar. Within these study areas, 19 candidates for REZ are identified based on the overlap between these study areas and upazilas (i.e., administrative subdivisions) containing economic development zones. Four of the identified candidate zones are opportunities for priority development, given the combination of strong wind and solar resources and the presence of economic zones. Furthermore, the geographic diversity of wind and solar resources in Bangladesh could help increase grid resilience by not concentrating all renewable energy development in the same region. Finally, pairing REZ with economic zones can bolster economic development, take advantage of large electricity demand, and leverage existing infrastructure investments.

Bangladesh↗

DOE OSTI2024

Baseload Hydrogen Production Using Nuclear and Renewable Energy: A Comparative Analysis

As the global push towards net zero carbon gains momentum, the demand for clean hydrogen is expected to grow rapidly across various sectors, including transportation, industries and electrical grids. To meet this growing hydrogen demand, baseload hydrogen production facilities capable of providing a continuous and reliable supply of hydrogen will be necessary throughout the world. This paper explores the technoeconomic feasibility of establishing baseload electrolytic hydrogen production facilities in the United States, utilizing different clean generation resources. The key criteria include maintaining a consistent supply of clean hydrogen without putting baseload demand stress to already vulnerable power grid. In order to do that, the proposed facilities will host onsite clean power generation and energy storage technologies. The proposed facilities can capitalize on available investment and production incentives and have ability to export excess electricity to the utility at a bulk price. Several scenarios are considered based on the clean energy resources to support the electrolysis process including light water reactors (LWRs) currently evaluating retirement options, wind, solar PVs, and advanced small modular reactors (SMRs). For each scenario, a hypothetical hydrogen production facility is considered in a location in the US where the primary generation resource is at its peak strength. Comparative analysis in this paper reveal that the nuclear power plants are most economically viable for baseload hydrogen production facilities, outperforming renewable-based facilities with significantly lower levelized cost of hydrogen (LCOH). Even under best-case scenarios for resource availability, incentives and export prices, renewable-based facilities face challenges due to daily and seasonal generation variability, resulting in large installation sizes and lower capacity factors. Among renewable-based facilities, complementarity hybrids, providing more stable power supply, demonstrate superior economics compared to facilities based on a single renewable technology. While LWR-powered facility can achieve a negative LCOH with incentives, SMR-powered facilities can provide economic hydrogen supply with LCOH below $1/kg with high temperature electrolysis option. The analysis in this paper underscores the pivotal role of nuclear energy in the future hydrogen economy.

08 - HYDROGEN↗