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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 73 records · Page 4
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DOE OSTI2021

Bias Characterization, Vertical Interpolation, and Horizontal Interpolation for Distributed Wind Siting Using Mesoscale Wind Resource Estimates

Much like their counterparts in utility-scale wind energy, developers of industrial, small-scale and distributed wind turbine deployments need to understand and accurately characterize the wind resource to properly assess the power generation and financial ramifications during siting and planning. National Renewable Energy Laboratory’s WIND (Wind Integration National Dataset) Toolkit (WTK) provides a best-in-class wind resource dataset generated using the Weather Research and Forecasting (WRF) model. This dataset includes parameters such as the wind speed, wind direction, and temperature at various heights, plus atmospheric stability near the surface. This data is available at 2-km spatial resolution and five-minute temporal resolution across 7 years, from 2007 to 2013 through a publicly accessible API interface. The Tools Assessing Performance (TAP) project seeks to extend this dataset to allow long term resource estimates and leverage it to better equip distributed wind equipment manufacturers, owner-operators, and installation professionals with better tools for practical siting applications. In this report, we present the results from our investigation within the TAP project focused on characterization of bias in WTK-based wind speed estimates and evaluation of vertical and horizontal interpolation techniques. We discuss the tradeoffs between different techniques and their combinations, as well as describe the lower bounds we determine for the studied validation errors. While the specific estimates we present are specific to WTK and the validation dataset we have chosen for this investigation (NREL's Wind Resource Meteorological Database), the overall analysis and the studied techniques are general enough to be applied to a broader set of wind datasets, both simulation-based and observational.

17 WIND ENERGY↗
DOE OSTI2024

Journey Mapping Distributed Wind Deployment: Installer Perspectives

This work uses journey maps to assess the deployment of distributed wind technologies through the perspective of installers. Journey mapping is a human-centered design method that chronologically traces processes from the perspective of those who participate in them. The journey map will be leveraged to identify deployment pain points (i.e., manifestations of generic deployment barriers) that the Strategize, Engage, Network and Deploy (SEND) Distributed Wind project team will seek to address in future work.

17 WIND ENERGY↗
DOE OSTI2026

FINAL PROJECT REPORT SBIR Phase II Next Generation Power Converters for Distributed Wind Applications

Intergrid, LLC, based in Temple, New Hampshire, conducted an 24-month DOE SBIR Phase II research program to develop next-generation electronic power inverters and converters for the United States distributed wind (DW) market. The distributed wind segment is defined as turbines rated from 10 kW to 1 MW, a market segment that has been almost entirely blocked by the absence of UL1741-certified, commercially available inverters.

17 WIND ENERGY↗
DOE OSTI2021

MIRACL Co‐Simulation platform for control and operation of distributed wind in microgrid

Abstract This paper presents a co‐simulation platform (CSP) developed as a part of the “Microgrids, Infrastructure Resilience and Advanced Controls Launchpad (MIRACL)” project, hereafter called MIRACL‐CSP, to allow simulation‐based testing, demonstration, and evaluations of distributed wind under various grid operating conditions. MIRACL‐CSP provides modular interactions among the power distribution system, distributed wind, and utility decision‐making framework. A hierarchical engine for large‐scale infrastructure co‐simulations (HELICS) is used as the core engine of MIRACL‐CSP to establish time and information coordination among the MIRACL‐CSP modules. In this study, MIRACL‐CSP performance is demonstrated using the IEEE 123‐node test distribution grid modelled in GridLAB‐D and the utility decision support application modelled in Python. The functionality of MIRACL‐CSP is demonstrated through various grid operational scenarios in a microgrid and networked microgrid environment. A co‐simulation study is described that demonstrated MIRACL‐CSP capabilities for the microgrid operational scenario in the IEEE 123‐node test system. MIRACL‐CSP is a generic platform that facilitates distributed wind research for different test systems, applications, and valuation of distributed wind.

17 WIND ENERGY↗
DOE OSTI2024

Design Load Basis Guidance for Distributed Wind Turbines

Aeroelastic modeling (AM) is the primary methodology for structural and performance assessment of any wind turbine. Nonetheless, the use of AM in the distributed wind (DW) industry sector is limited due to several challenges (Damiani, Davis, & Summerville, 2022). One of these challenges lies in the perceived complexity of generating a proper set of numerical simulations to extract and process the key outputs for component design and verification, and, ultimately, achieve certification. This makes it difficult to reliably predict the structural and performance response of small wind turbines. From the investigation carried out in (Damiani & Davis, 2022), it is apparent that many stakeholders in this sector believe that a comprehensive guide for developing a design load basis (DLB) for distributed wind turbines (DWTs) is necessary.

17 WIND ENERGY↗
DOE OSTI2024

Distributed Wind for Industrial Loads

Industrial loads have significant energy resilience requirements, which is one reason distributed wind may be a good option to help provide generation for these facilities. This fact sheet provides an overview of industrial load energy and resilience needs, and discusses why distributed wind may be a good option to provide onsite power for these facilities.

17 WIND ENERGY↗
DOE OSTI2024

Towards a Workforce Roadmap for Distributed Wind: Phase 1 - Identifying Needs and Barriers

Despite recent policy, research efforts, and resources available for utility-scale and offshore wind workforce development, the distributed wind (DW) industry has yet to make similar advances to address its workforce challenges. This report initiates the phased development of a DW workforce roadmap to provide a foundation for roadmap development. Phase 1, contained in this report, uses desk-based research on clean energy workforce approaches and a DW interested-party survey to discuss needs and barriers hindering the workforce from expanding. Findings are summarized into goals and solutions for Phase 2 of roadmap development, which identifies actors responsible for implementing solutions identified in Phase 1. Phase 1 results suggest that the sector's small size and limited growth motivate the short-term need for skilled workers or candidates with well-rounded and multifaceted abilities. Long-term expansion plans must diversify positions while capitalizing on existing utility-scale wind and offshore workforce efforts, as well as other renewable sector best practices where possible. The findings in this report can advance workforce development in the DW sector by aligning interested industry parties around common goals to address challenges. Training providers, installers, operators, manufacturers, federal agencies, national laboratories, academic partners, and labor unions can utilize the findings to help promote sustainable growth of the DW sector.

17 WIND ENERGY↗
DOE OSTI2021

Distributed Wind Considerations from the IEEE 1547-2018 Revision

The revision of the U.S. interconnection Standard IEEE 1547 in 2018 (IEEE 1547-2018) has added new interconnection and interoperability requirements for grid-connected distributed wind generators (DWG / wind turbines) and all other distributed energy resources (DERs). These new requirements will enable distributed wind generators to provide greater benefits to electric grid operators and DER operators, but also presents new challenges for the testing and certification of DWG systems. This report provides a summary of recent interconnection standard revisions from a DWG perspective, outlines the potential benefits to the power system from the revisions, evaluates the main concerns from a DWG manufacturer’s perspective, and provides general industry guidance related to IEEE 1547-2018 adoption.

17 WIND ENERGY↗
DOE OSTI2022

Challenges and Possible Solutions in Aeroelastic Modeling for the Distributed Wind Industry

Aeroelastic modeling (AM) is the primary methodology for structural and performance assessment of any wind turbine; it provides an understanding of the impact of design parameters on turbine loading and power response before witnessing it in the field. Despite these advantages, the use of AM in the distributed wind technology (DWT) sector is limited. This article represents a short summary of an in-depth assessment by the authors of the status of AM and its role within the distributed wind technology design standards. The research gathered input and feedback from a large number of U.S. and international stakeholders, reviewed technical strengths and weaknesses of the current edition of the design standards, analyzed the minutes from recent industry workshops and meetings, collected publicly available AM templates, and provided an evaluation of the existing AM codes. Several goals were achieved including providing strategies for the load assessment categorization of turbines based on rotor swept area and archetype, and guidance for AM verification and validation. Recommendations within this study will advance the value and the ease-of-use of AM, thereby allowing the industry to better capitalize this underutilized tool, resulting in a more efficient design process, an easier path to certification, and overall better and more reliable distributed wind technology products.

17 WIND ENERGY↗
DOE OSTI2024

Distributed Wind Brings Value to Communities

Value streams extend beyond traditional quantitative metrics and benefit a variety of stakeholders. When considering a distributed wind system, both the benefits and costs of the potential system need to be well understood. This fact sheet provides an overview of how to value the various benefits of distributed wind systems.

17 WIND ENERGY↗
DOE OSTI2021

Distributed Wind Resilience Metrics for Electric Energy Delivery Systems: Comprehensive Literature Review

While most people have a general concept of what it means to be “resilient,” an examination of definitions from different sources reveals that there are key commonalities but key differences as well. The lack of a generally accepted definition and application of resilience extends to electric energy delivery systems. Without an accepted definition, it is difficult to implement programs or processes to improve resiliency. In this paper, existing work from industry, regulatory bodies, and national laboratories to define and apply resilience to electric energy delivery systems is studied to understand the key components to define resilience and better understand associated metrics. This understanding is then applied to distributed wind for a specific example of how resilience of a system is affected by the technologies and generation sources used to support it. A key finding is that there is no “one size fits all” process for resilience. Each system has a “distinctiveness” characteristic, which qualifies the possibility of differences in resilience due to different threats, geography, stakeholders, risk tolerance, and mitigations. The distinctiveness characteristic extends to distributed wind, where different configurations may lend the distributed wind to contribute to the resilience of systems in a variety of ways. The findings of this research demonstrate the need for a resilience framework that can be readily applied by stakeholders to improve resilience based on the specific system, threat, risk tolerance and stakeholders.

17 WIND ENERGY↗
DOE OSTI2021

Deliverable D12 – Distributed Wind Data Catalog Development Guide and Instruction Manual

Pacific Northwest National Laboratory and Technical University of Denmark completed this deliverable as part of Work Package 2: Data Information Catalog for Distributed Wind Research (WP2) for the International Energy Agency Wind Technology Collaboration Programme Task 41: Enabling Wind to Contribute to a Distributed Energy Future (IEA Wind Task 41). As the final deliverable for WP2, Deliverable D12 includes a data instruction guide for the IEA Wind Task 41 distributed wind data catalog. As such, this document includes: a step-by-step explanation of how the IEA Wind Task 41 data catalog was created, how it was populated, and how to use it; future options for the IEA Wind Task 41 data catalog, and a summary with recommendations for future work.

17 WIND ENERGY↗
DOE OSTI2020

California Time-of-Use (TOU) Transition: Effects on Distributed Wind and Solar Economic Potential

Time-of-use (TOU) retail energy rates price electricity differently by the time of day, communicating to consumers the costs of supplying electricity diurnally. This study evaluates the impact of Decision D.15.07-001, which mandates a transition in 2020 to default TOU rates for residential ratepayers in California, on the economic viability of behind-the-meter distributed wind and solar systems. Previous studies have demonstrated that increasing wind and solar generation will materially affect the diurnal cost of wholesale electricity. As retail and wholesale prices become more aligned, this could affect the inter-technology economic viability of distributed generation. We assess economic viability through 'economic potential,' or the amount of generation capacity that exceeds a rate of return of 5.4%. In addition, we identify sensitivities of economic potential to capital costs and other techno-economic factors as well as the specific counties and sectors with substantial economic potential. We find that TOU implementation is projected to moderately increase economic potential of distributed wind and marginally decrease that of distributed solar. Over the long-term as variable renewable energy penetration increases in California, particularly utility-scale solar, net peak load and thus peak prices will shift later in the evening. To the extent that retail rates continue to evolve with wholesale prices, we find the changes could positively affect the value of wind generation more than that of solar generation. Over the scenarios considered, model results indicate realistic pathways to reaching a robust distributed wind market in California though solar economic potential was found to be substantially larger than that of wind.

17 WIND ENERGY↗
DOE OSTI2023

Distributed Wind Aeroelastic Modeling (dWAM)

Aeroelastic modeling is the primary method for the structural and performance assessment of any wind turbine. Despite the advantages afforded by aeroelastic modeling tools, their use in the distributed wind energy industry is limited. dWAM started from the NREL Aeroelastic Modeling for Distributed Wind Turbines project with Damiani & Davis (2022) researching current needs, including input from an industry workshop. NREL's efforts will focus on OpenFAST code improvements, validation using research turbines at NREL's Flatirons Campus, code-to-code verification activities, and development of guidance documents and improved user manuals. Partner lab, Sandia National Laboratories, will focus their efforts on vertical axis wind turbine (VAWT) modeling including modeling code development, validation, and user-experience improvements.

aeroelastic↗
DOE OSTI2021

Technology Innovation Pathways for Distributed Wind Balance-of-System Cost Reduction

This exploratory analysis characterizes the balance-of-system (BOS) cost reduction opportunity for small, commercial, medium, and large distributed wind systems. To do this, we used the National Renewable Energy Laboratory’s (NREL’s) Land-based Balance of System Systems Engineering (LandBOSSE) model (Eberle et al. 2019). This model calculates the capital expenditures (CapEx) associated with installation and the system components (e.g., foundation and electrical infrastructure) other than the rotor nacelle assembly and tower. Then, building on the cost reduction potential assessment, we provide a more qualitative evaluation of prospective technology innovation concepts that may enable realization of those cost reductions for distributed wind systems.

17 WIND ENERGY↗
DOE OSTI2022

Advanced Distributed Wind Turbine Controls Series: Part 3-Wind Energy in Grid-Connected Deployments – Microgrids, Infrastructure Resilience, and Advanced Controls Launchpad (MIRACL)

In recent years the technical ability and requirement for distributed wind turbines to provide grid support services beyond maximum energy production has increased. Ancillary services leveraged through advance controls of a wind turbine support grid reliability and resilience. One ancillary service that is significant to a grid-connected wind turbine deployment is fault ride through (FRT) in response to the voltage and frequency events in the power system. As part of the Microgrids, Infrastructure Resilience, and Advanced Controls Launchpad (MIRACL) this paper demonstrates, through desktop simulations, the wind turbine's FRT capabilities to support stable grid operation. We establish that the wind turbine models exceed FRT performance requirements stipulated in IEEE 1547-2018, regarding interconnection and interoperability of distributed energy resources. Utilizing a standalone CART2 (600 kW) wind turbine connected to the NREL's Flatirons Campus grid, we study voltage and frequency FRT utilizing various test cases. One of the test cases under study is a Category III voltage fault defined in IEEE 1547-2018 and derived from CA Rule 21. Some distributed wind turbines were unable to connect to the grid following the Rule 21 enforcement in California. Even if this is not a general requirement elsewhere, the grid codes might evolve in this direction. This study illustrates how a distributed wind turbine can provide some of these FRT services and enable a pathway toward a higher contribution of renewable energy in a distribution grid.

17 WIND ENERGY↗
DOE OSTI2022

Aeroelastic Modeling for Distributed Wind Turbines: March 11, 2021 - November 10, 2021

Aeroelastic modeling (AM) is the primary methodology for structural and performance assessment of any wind turbine whereby providing an understanding of the impact of design parameters on its loading and power response before witnessing it in the field. Despite these advantages, the use of AM in the Distributed Wind Technology (DWT) sector is limited, especially within the less established manufacturers. This project represents an in-depth assessment of the status of AM and its role within the Standards for the DWT industry. The study gathered input and feedback from a large number of national and international stakeholders, reviewed technical strengths and weaknesses of the current edition of the design standards, analyzed recent industry workshops' and meetings' minutes, collected publicly available AM templates, and provided an evaluation of the existing AM codes. The study achieved several goals including providing strategies for the load assessment categorization of turbines based on rotor swept area and archetype, and guidance for AM verification and validation (V&V), which includes discussions of measurement requirements and a sample test-plan useful for future V&V campaigns and design standard development. This document summarizes the different tasks conducted in the course of the project and highlights the steps required to improve the AM adoption based on a multifaceted approach that encompasses: 1) augmenting AM software capabilities, 2) publishing AM best-practices and design-basis, 3) creating new model templates, 4) providing guidance for V&V of codes and specific turbine models leveraging field testing best-practice, and 5) addressing weaknesses in the current standards. Many of the future objectives identified in this study could leverage NREL's upcoming testing campaigns of three modern distributed wind turbines. Recommendations within this study will advance the value and the ease-of-use of AM, thereby allowing the industry to better capitalize this underutilized tool resulting in a more efficient design process, an easier path to certification, and overall better and more distributed reliable wind turbine products.

17 WIND ENERGY↗