the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 26 Nov 2024
A parcel-level evaluation of distributed wind opportunity in the contiguous United States
Abstract. This study examines the potential for distributed wind (DW) energy across the contiguous United States, leveraging advancements in the National Renewable Energy Laboratory's distributed wind model, dWind. The novel modeling approach described here utilizes a high-resolution dataset and analyzes over 150 million parcels, a significant improvement from prior methods that extrapolated results from a smaller random sample. This achievement is enabled through key model performance improvements, such as transitioning to parallel processing, which reduces runtime by 97 %. This optimized, high-resolution approach allows the inspection of technology deployment potential and impact on a variety of scales tailored to individual properties and regions. The results here align with prior work showing substantial opportunity for energy generation using DW technologies. Key findings reveal a substantial increase from prior results in estimated technical and economic potential for DW. Metrics tuned to highlight economic potential also show increased incentives supporting rural adoption. Results are spatially aggregated for usability and published via the U.S. Department of Energy Wind Data Portal and a custom scenario visualization platform, aiding policymakers, industry, and property owners in assessing DW viability across various scenarios and spatial scales.
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Status: open (until 01 Jan 2025)
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RC1: 'Comment on wes-2024-147', Anonymous Referee #1, 17 Dec 2024
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The manuscript makes a strong contribution with respect to modeling and analysis capabilities for future distributed wind deployment. The authors articulate the advances from the previous model to the current one and the impressive gains in computational efficiency. The paper is clearly structured and well written. However, the Introduction and Discussion sections are underdeveloped, and more references are needed throughout. The Introduction would benefit from an explanation of why the new approach provides a contribution to the users of this information (i.e., how does someone who is looking at potential deployment for distributed wind benefit from the model using parcel-level data relative to the previous sample approach?) and a clear objective for the paper. The Discussion should address that same idea within the context of interpreting the results, and some narrative that describes the limitations should be added. The authors should also establish the broader value of the work to the international community given the journal’s scope.
Specific Comments:
- The commentary on RAISE is misleading. RAISE did not directly make additional funds available to end users considering DW installation. RAISE is an initiative, not an incentive, so a customer cannot be eligible or ineligible for the RAISE initiative. I think you may be referring to USDA’s REAP eligibility. Please clarify.
- Line 21: Distributed wind can encompass more than turbines up to 60m in height. Please clarify if you are choosing to define DW this way because of your model structure or provide a resource that backs this. References you cite show there is more range than this.
- Line 83: Potential missing word in “account for is and revenue streams”
- Line 95: This sentence is long, and its intention unclear. With the workflow critical to understanding the paper’s contribution, I recommend rephrasing and better aligning the language with Figure 1 to maximize the figure’s usefulness.
- Table 1: In addition to descriptions of the datasets that are used, this section needs a discussion around why these specific sources were selected over others and which ones were used in the original model compared to the new version that this paper covers.
- Line 116: Define CPU
- Line 117: Define I/O
- Line 159: Why is only one turbine sited? What are the limitations of this approach?
- Figure 4: This figure needs a legend defining what the magnitude of the circles represents. I also recommend using a higher resolution figure if it is available.
- Line 190: Which of the cities are respectively urban, suburban, and rural? What makes these cities representative of those environments?
- Figure 7: Does this show the scenarios where the largest turbine is sited or sized to load? Please specify.
- Table 5 and Table 6: These tables are dense and include many N/A values. I recommend restructuring or parsing to make them to make the intention of the tables clear.
- Line 402: You don’t make any direct comparisons between your model outputs (or assumptions) and existing deployment to illustrate that the deployment potential is untapped.
Citation: https://doi.org/10.5194/wes-2024-147-RC1
Data sets
Distributed Wind Model Results Caleb Phillips https://a2e.energy.gov/project/dw
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