Wind Farm Layout Patents: Who Leads, Where the Gaps Are 2026
- Filings have plateaued, not grown. activity peaked in 2024 at 5 filings after a flat midpoint in 2022, so the field is not accelerating the way turbine deployment volumes might suggest.
- The claim space has moved off pure hardware. F03D (wind motors) still anchors 13 of 15 records, but G06Q, G06N and G06T entries show layout and siting work increasingly framed as data-processing and AI method claims, not mechanical ones.
- Assignee momentum has gone quiet. every tracked assignee, including GE, IBM and multiple Chinese universities, shows zero filings in the latest tracked year — a sign publication lag is masking recent activity rather than the field going cold.
What this landscape covers
Wind farm layout and siting optimization sits at the intersection of two claim traditions: mechanical wind-turbine engineering under F03D, and computational siting methods increasingly filed under G06Q, G06N and G06T. The search set captures patents and applications that combine wake-effect language with siting-specific terms such as turbine spacing, wind resource assessment and annual energy production, narrowed to the wind-motor and business-method IPC classes most relevant to layout decisions.
Fifteen published families span 2015 through the partial 2026 window, filed mainly through the United States and China with a smaller presence in the United Kingdom, Europe and India. The dataset is small enough that individual filings move the picture meaningfully, so rankings and trend lines here should be read as directional rather than exhaustive.
Filing trends and technology composition
Two views of the same 15-family dataset: how filing volume has moved year over year, and which IPC subclasses carry the claim weight.
Flat-to-declining filing trend
Filings rose from 2 in 2017 to a peak of 5 in 2024, with 2022 sitting at the midpoint value of 4. There is no sustained upward trend across the window, and the most recent year is necessarily undercounted because publication typically lags filing by around 18 months.
F03D dominates, but data-processing classes are rising
F03D (wind motors) covers 13 of 15 records and remains the anchor class for turbine-level siting claims. The presence of G06Q, G06F, G06K, G06N and G06T across the remainder shows a meaningful share of recent filings claim siting as a computational or data-analysis method rather than as turbine hardware or arrangement.
Shares are the percentage of the 15 records in scope. A patent can carry several IPC classes, so the shares add up to more than 100%.
Go deeper on Wind Farm Layout and Siting Optimization with Eureka
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Try EurekaThe most-cited records in this landscape
Mapping wind turbines and predicting wake effects using satellite imagery data
Methods, systems, and computer program products for mapping wind turbines and predicting wake effects using satellite imagery data are provided herein. A computer-implemented method includes analyzing one or more satellite images depicting one or more portions of a pre-determined geographic area; detecting a group of one or more wind turbines in the pre-determined geographic area based on the analyzing step and one or more additional items of data; inferring geographic coordinates of each of the detected wind turbines; predicting a wake effect impacting one or more of the detected wind turbines based on the inferred geographic coordinates of each of the detected wind turbines and forecasted…Filed by International Business Machines Corporation; granted 2019-08-20.
| # | Publication no. | Patent title | Citations |
|---|---|---|---|
| 1 | US20180336408A1 | Mapping Wind Turbines and Predicting Wake Effects Using Satellite Imagery Data | 15 |
| 2 | CN108533454A | 有功输出调节下的风电场机组疲劳均匀分布的优化控制方法 | 12 |
| 3 | US20230049193A1 | Wind turbine layout optimization method combining with dispatching strategy for wind farm | 9 |
| 4 | US10387728B2 | Mapping wind turbines and predicting wake effects using satellite imagery data | 9 |
| 5 | CN118246820A | 一种上下游风场风资源评估与发电量计算方法及系统 | 7 |
| 6 | US20250146470A1 | Method for optimizing wind farm electric power generation using multivariable system identification | 3 |
| 7 | GB2623596A | Wind farm control | 2 |
| 8 | CN121172828A | 一种多方向尾流效应的非阵列式风电场储能系统配置方法 | 1 |
Citation counts reflect influence within the searched corpus and skew toward older filings; they are not a measure of current commercial relevance.
Patent titles are shown in the language they were filed in, not translated, so that each record stays verifiable against the original filing — a translated title will not match in Eureka or in any national register. Publication numbers are shown where the record carries one (8 of 8 rows); clicking a row searches Eureka by that number.
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Browse MCP servers →What the numbers mean for filing strategy
Three read-throughs from filing trend, citation pattern and jurisdiction split that matter more than the raw counts.
Growth has stalled, not accelerated
The 2017-to-2026 trend rises to a 2024 peak of 5 filings before dropping toward the partial 2026 count, with 2022 sitting at the midpoint of 4. That is a plateau pattern, not a growth curve — filing pressure in this specific claim space has not kept pace with global wind capacity additions.
Satellite-based turbine mapping anchors the field
The two most-cited records both concern mapping wind turbines and predicting wake effects from satellite imagery, filed by the same assignee family. Their citation lead over the rest of the set suggests this approach set the vocabulary the later Chinese filings on wake-effect control and resource assessment now build against.
Filing is concentrated in two markets
The United States and China together receive 11 of the 15 records, with the UK, EPO and India accounting for the remainder. Anyone clearing freedom-to-operate for a siting tool aimed at a European or Indian deployment is working against a thinner, less-tested prior-art base than in the US or China.
Eureka can read the same corpus for gaps instead of for coverage: under-claimed branches adjacent to wind farm layout and siting optimization, with the prior art for and against each one.
Who is filing, and where the field is open
The assignee set is a mix of a large-technology incumbent, Chinese universities and grid operators, and specialist consultancies — none showing filings in the latest tracked year, which is more consistent with publication lag than with abandoned interest.
IBM's satellite-mapping approach
International Business Machines Corporation holds the most-cited record in this set, built on inferring turbine positions and wake effects from satellite imagery rather than site-installed sensors. No filings in the latest tracked year fit the broader publication-lag pattern seen across every assignee here.
Chinese universities working control and layout angles
Zhejiang University and Central South University both appear in the assignee set, pointing to sustained academic interest in wake-effect control and layout optimization methods rather than a single dominant industrial player.
A single cross-institution collaboration
The only recurring co-assignee pairing in the dataset links Shenzhen Shifeng Technology Co., Ltd. (Shenzhen Shifeng Technology) with PowerChina Northwest Engineering Corporation Limited (PowerChina Northwest Engineering Corporation), pairing a specialist technology firm with an engineering design institute on resource-assessment and generation-calculation methods.
| Assignee | Recent year | YoY |
|---|---|---|
| General Electric Infrastructure Technology LLC | 0 | — |
| Zhejiang University | 0 | — |
| Hangzhou Taiji Yucai Software Co., Ltd. | 0 | — |
| International Business Machines Corporation (IBM) | 0 | — |
| Central South University | 0 | — |
| FRAZER-NASH CONSULTANCY LTD | 0 | — |
| Shenzhen Shifeng Technology Co., Ltd. | 0 | — |
| State Grid Shandong Electric Power Company | 0 | -100% |
Where to take this
The dataset points to a small, technically active field where the next moves depend on which side of the hardware/software split a filer sits on.
Model the wake-effect / AI-siting boundary
With F03D still dominant but G06Q, G06N and G06T carrying a growing share, method claims framed around AI-based siting or wake prediction warrant their own freedom-to-operate pass separate from turbine-hardware clearance.
Explore in Eureka →Track publication-lag masked activity
Every assignee shows zero filings in the latest tracked year; that is expected given an 18-month typical publication lag, not evidence the field has gone quiet. Re-run the trend analysis in 6–12 months as the 2025–2026 cohort publishes.
Explore in Eureka →Test the under-claimed branches
Real-time dispatch-linked re-optimization and multi-farm wake interaction across ownership boundaries show thin direct coverage in this set relative to adjacent single-farm wake modeling work.
Explore in Eureka →Common questions on wind farm layout and siting patents
This landscape identifies 15 published patent families matching wake-effect, turbine-spacing and siting-method search terms within the relevant wind-motor and business-method IPC classes, filed between 2015 and mid-2026. That is a small, tightly defined set rather than the full body of wind-energy patents, because the search deliberately narrows to layout and siting language rather than general turbine design. Broader wind-turbine patenting, including blade design, drivetrain and grid-interconnection hardware, sits outside this count entirely.
The assignee set mixes an established technology incumbent, International Business Machines Corporation, with Chinese academic institutions such as Zhejiang University and Central South University, plus specialist firms and grid operators. No single assignee dominates the 15-family set the way a market leader typically does in a mature patent landscape. That thin concentration means a new entrant is not necessarily filing against one blocking incumbent, but against a scattered set of method claims spread across several organizations.
US10387728B2, assigned to International Business Machines Corporation and granted in August 2019, claims a computer-implemented method for detecting wind turbines in satellite imagery, inferring their geographic coordinates, and predicting wake effects impacting those turbines based on forecasted conditions. It is a data-analysis and prediction method rather than a physical turbine or layout arrangement claim. Anyone building a satellite-imagery-based turbine detection or wake-prediction pipeline should read its claim scope carefully before assuming a clear path, since it is the most-cited record in this landscape.
Yes — the IPC composition in this dataset shows a real and growing share of filings classified under G06Q, G06N, G06F and G06T, meaning siting and wake-prediction methods are being claimed as computational processes rather than as turbine hardware. Whether a specific method clears patentability in a given jurisdiction depends on how tightly it is tied to a practical application, such as a specific data source or output used to control turbine placement or dispatch. The presence of granted US and Chinese filings in this space indicates examiners have allowed such claims when the technical implementation is specific enough.
The current 15-family set shows thin direct coverage of multi-farm wake interaction across ownership boundaries, real-time dispatch-linked layout re-optimization, and grid-constrained siting tied to power-delivery limits under H02J. These sit adjacent to well-covered single-farm wake modeling and satellite-based turbine mapping work, suggesting claim space that has not yet been fully staked out. Given the small size of this dataset, a well-drafted claim in one of these branches would face a comparatively shallow prior-art landscape today.
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Disclaimer. This page is generated from Patsnap Eureka data drawn from a limited snapshot of global patent and scientific-literature records, and is provided for general information and reference only.
Patent data carries inherent limitations: recent filings (typically the most recent 18–24 months) are under-counted due to standard publication lag; counts may be reported at either a patent-family or a patent-record basis and are not always directly comparable; classification, applicant-name, and citation data may contain errors, duplicates, or omissions; and the underlying search query defines and constrains the scope shown. As a result, the analysis may be incomplete or inaccurate and may not reflect the full technology landscape.
Nothing on this page constitutes an exhaustive prior-art, novelty, freedom-to-operate, or validity search, nor does it constitute legal, financial, investment, or professional advice, and it should not be relied upon as such. Any patent, commercial, or strategic decision should be verified independently and reviewed with qualified patent, legal, and domain professionals. Patsnap makes no warranties, express or implied, as to the accuracy, completeness, or fitness for any particular purpose of the information presented.
Machine translation. Assignee and organisation names originally recorded in Chinese, Japanese or Korean have been rendered into English by an AI translation step so that the tables stay readable. These renderings are best-effort and may not match a company’s registered English name; the original name is what the underlying patent record carries, and it is what any Eureka query launched from this page uses.