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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Interactions of Wind Energy Project Siting, Wind Resource Potential, and the Evolution of the U.S. Power System

The interactions of wind energy project siting, resource potential, and power system evolution are critical to understand given interest in high renewable energy systems, particularly as wind costs have fallen and grid operators implement solutions to manage variable generation. This study applies an integrative approach that combines spatially-explicit resource potential analysis with high spatial resolution U.S. electricity system modeling. Multiple wind supply curves, representing variations in siting regimes that account for interactions with built infrastructure, regulatory, physical, and social land use factors, are evaluated to determine how siting could influence prospective wind development. Different siting regimes lead to variations in future wind capacity, with the greatest impacts observed under scenarios with high demand for clean energy. With the tightest emissions limit modeled, 2050 onshore wind capacity varied by +7% (49 GW) in the least-restrictive siting regime to a decrease of 37% (270 GW) under the most-constrained case. More-stringent siting restrictions lead to higher electricity prices and emissions that should be weighed with local impacts. Under restrictive siting regimes, wind deployment is also sensitive to transmission availability and wind plant design. Overall, the findings highlight the importance of local land use considerations in regional and national power system planning.

17 WIND ENERGY↗
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 OSTI2023

Wind RD&T: On Site Wind for Rural Load Centers

This presentation will provide an overview of the "On Site Wind for Rural Load Center" project for an FY23 research, development, and technology review with other Wind Energy Technologies Office researchers and DOE program managers. This copy of slides is appropriate for public release.

17 WIND ENERGY↗
DOE OSTI2022

U.S. Wind Siting Regulation and Zoning Ordinances

A machine readable collection of documented wind siting ordinances at the state and local (e.g., county, township) level throughout the United States. The data were compiled from several sources including, DOE's Wind Exchange Ordinance Database (Linked in the submission), National Conference of State and Legislatures Wind Energy Siting (also linked in the submission), and scholarly legal articles. The citations for each ordinance are included in the spreadsheet. This data is an updated to a previously developed database of wind ordinances found in OEDI Submission 1932: "U.S. Wind Siting Regulation and Zoning Ordinances"

analysis↗
DOE OSTI2018

Characterizing forecastability of wind sites in the United States

With the rapid growth of wind power, managing its uncertainty and variability becomes critical in power system operations. Wind forecasting is one of the enablers to partially tackle challenges associated with wind power uncertainty. To improve the 'forecasting ability', defined as forecastability, different forecasting methods have been developed to assist grid integration of wind energy. However, forecasting performance not only relies on the power of forecasting models, but is also related to local weather conditions and (known as wind characteristics) wind farm properties. In this study, geospatial and instance spatial distributions of six wind characteristics and two forecasting error metrics are first analyzed based on 126,000 + wind sites in the United States. Forecasts in different look-ahead times are generated by using a machine learning based multi-model forecasting framework model and the Weather Research and Forecasting model. A forecastability quantification method is developed by characterizing the relationship between forecastability and wind series entropy using three regression methods, i.e., linear approximation, locally weighted scatterplot smoother nonlinear nonparametric regression, and quantile regression. It is found that the forecastability of a wind site can be successfully characterized by wind series characteristics, thereby providing valuable information at different stages of wind energy projects.

17 WIND ENERGY↗
DOE OSTI2025

U.S. Wind Siting Regulation and Zoning Ordinances (2025)

A machine readable collection of documented wind siting ordinances at the state and local (e.g., county, township) level throughout the United States. The data were compiled using the Infrastructure Continuous Ordinance Mapping for Planning and Siting Systems (INFRA-COMPASS) tool, which leverages Large Language Models (LLMs) to automate the collection of local codes and ordinances applicable to energy infrastructure. URLs for the ordinance source documents are included in the Wind Ordinances spreadsheet. The GeoPackage file included below contains the jurisdiction shapes for each ordinance. Note that the GeoPackage file is formatted for ingestion by NREL's reVX setbacks tool and therefore does not contain any of the state-level regulations. NOTE: This data was collected with the help of generative AI. The Large Language Models used for this effort make mistakes. Always validate the data for critical use cases. This data is an update to a previously developed database of wind ordinances found in OEDI Submission 5733: see the "U.S. Wind Siting Regulation and Zoning Ordinances 2022" link below. INFRA-COMPASS version used for collection: v0.8.2 LLMs used for collection: GPT-4.1, GPT-4.1 mini, GPT-4.1 nano, GPT-4o mini

17 WIND ENERGY↗
DOE OSTI2019

U.S. Wind Siting Regulation and Zoning Ordinances

A collection of documented wind siting ordinances at the state, county, township, and local level throughout the United States. The data were compiled from several sources including, DOE's Wind Exchange Ordinance Database (https://windexchange.energy.gov/policies-incentives), National Conference of State and Legislatures Wind Energy Siting (https://www.ncsl.org/research/energy/state-wind-energy-siting.aspx), and scholarly legal articles. The citations for each ordinance are included in the spreadsheet.

A-weighted decibel↗
DOE OSTI2015

Small Wind Site Assessment Guidelines

Site assessment for small wind energy systems is one of the key factors in the successful installation, operation, and performance of a small wind turbine. A proper site assessment is a difficult process that includes wind resource assessment and the evaluation of site characteristics. These guidelines address many of the relevant parts of a site assessment with an emphasis on wind resource assessment, using methods other than on-site data collection and creating a small wind site assessment report.

17 WIND ENERGY↗
DOE OSTI2022

Comparative Study of Wind Energy Potential Estimation Methods for Wind Sites in Togo and Benin (West Sub-Saharan Africa)

The characterization of wind speed distribution and the optimal assessment of wind energy potential are critical factors in selecting a suitable site for wind power plants (WPP). The Weibull distribution law has been used extensively to analyze the wind characteristics of candidate WPP sites, and to estimate the available and deliverable energy. This paper presents a comparative study of five wind energy resource assessment methods as they applied to the context of wind sites in West Sub-Saharan Africa. We investigated three numerical approaches, namely, the adaptive neuro-fuzzy inference system (ANFIS), the multilayer perceptron method (MLP), and support vector regression (SVR), to derive the distribution law of wind speeds and to optimally quantify the corresponding wind energy potential. Next, we compared these three approaches to two well-known Weibull distribution law-based methods: the empirical method of Justus (EMJ) and the maximum likelihood method (MLM). Case study results indicated that the neural network-based methods, ANFIS and MLP, yielded the most accurate distribution fits and wind energy potential estimates, and consequently, are the most recommended methods for the wind sites in Togo and Benin. The orders of magnitude of the root mean squared error (RMSE) in estimating the recoverable energy using ANFIS were, respectively, 10-4 and 10-5 for Lomé and Cotonou, while MLP achieved an RMSE order of magnitude of 10-3 for both sites.

17 WIND ENERGY↗
DOE OSTI2023

On Site Wind for Rural Load Centers

This slide deck shares an overview of the On Site Wind for Rural Load Centers project, its relevance to the distributed wind community, and stakeholder engagement efforts.

17 WIND ENERGY↗
DOE OSTI2019

Oregon Offshore Wind Site Feasibility and Cost Study

The work performed in this Oregon study assessed the present and future costs of floating offshore wind technology deployment in the state of Oregon at commercial scale. It is widely recognized that floating offshore wind energy technology will be needed if significant offshore wind deployment in the Pacific region is to occur. The study was performed by the National Renewable Energy Laboratory (NREL) and its subcontractors and funded by the Bureau of Ocean Energy Management (BOEM). It was based, in part, on assumptions and analysis from an NREL report titled 'A Spatial-Economic Cost-Reduction Pathway Analysis for U.S. Offshore Wind Energy Development from 2015-2030' (Beiter et al. 2016), which supported the 'National Offshore Wind Strategy' (Gilman et al. 2016). The strategy builds on the previous DOE Wind Vision Study Scenario of 86 gigawatts (GW) of offshore wind deployed by 2050 in the United States. Under the Wind Vision scenario, 20% (17.2 GW installed capacity) of the nation's total offshore wind in 2050 comes from the Pacific coastal states (DOE 2015), which will require the development of floating wind technologies. Although most offshore development to date has been in depths of 50 meters (m) or less, 97% of Oregon's offshore wind resource is in water depths greater than 60 m, where floating wind is assumed to be needed. Floating offshore wind technology is still in its nascent stage of development but is advancing toward commercialization in both Europe and Asia. In this report, we use available floating prototype costs, pilot-scale costs, and commercial-scale costs from fixed-bottom offshore wind projects to model and analyze the cost of floating wind for five hypothetical wind sites in Oregon using specific geographical and utility grid information.

17 WIND ENERGY↗
DOE OSTI2023

On Site Wind for Rural Load Centers: RADWIND community presentation

These slides will be presented to the RADWIND workshop attendees at the pre-conference workshop of the NRECA TechAdvantage Experience. This presentation gives an overview of the On Site Wind for Rural Load Centers project in order to inform participants of ongoing work in the distributed wind space and share opportunities to get involved.

17 WIND ENERGY↗
DOE OSTI2019

Oregon Offshore Wind Site Feasibility and Cost Study

The focus of this presentation is to: Reflect current floating wind technology trends and industry market data in cost models; Provide cost analysis in support of Oregon state energy planners considering floating offshore wind's potential contribution to future state energy supplies.

17 WIND ENERGY↗
DOE OSTI2019

Optimizing wind farm siting to reduce power system impacts of wind variability

We introduce and solve two variants of a biobjective optimization model to reduce the negative impact of wind variability on the power system by strategically locating wind farms. The first model variant considers average changes in wind power over time; the second captures extreme fluctuations in wind power. A complementary set of wind sites is selected with the aim of minimizing both residual demand and the variability in residual demand. Because exact optimization is computationally intensive, we develop two heuristics—forward and backward greedy algorithms—to find approximate solutions. The results are compared with the exact optimization results for a well-selected subset of the data as well as to the results from selecting sites based on average wind alone. The two models are solved using demand data and potential wind sites for the Southwest Power Pool. Though both objectives can be improved by adding more sites, for a fixed number of sites, minimizing residual demand and variability in residual demand are competing objectives. Here, we find an approximate efficient frontier to compare trade-offs between the two objectives. We also vary the parameter in the heuristic that controls how the two objectives are prioritized. For the case study, the backward greedy algorithm is more effective at reducing the wind power variability than the forward greedy algorithm. Furthermore, using the backward algorithm for the full dataset is more effective than solving the exact optimization on a subset of the data when the results are evaluated using the full dataset.

17 WIND ENERGY↗
DOE OSTI2013

Building Toward a Small Wind Turbine Site Assessor Credential (Presentation)

Proper site assessment is integral to the development of a successful small wind project. Without a small wind site assessor certification program, consumers, including state incentive program managers, lack a benchmark for differentiating between qualified and nonqualified site assessors. A small wind site assessor best practice manual is being developed as a resource for consumers until a credential program becomes available. This presentation describes the purpose, proposed content, and the National Renewable Energy Laboratory's approach to the development of such a manual.

17 WIND ENERGY↗