Virtual Power Plant Simulation Patents: Leaders & Trends 2026
- Filing only started in earnest after 2022 and the dataset's peak year (23 families) is the most recent full year on record — this is an early-innings field, not a settled one.
- One jurisdiction dominates the filings China accounts for 38 of the 44 records, with South Korea and the United States each contributing a handful — a strong signal for where prior art risk concentrates.
- Business-process claims outnumber grid-hardware claims G06Q (business/commerce data processing) appears in 38 records versus 28 for H02J (power grid systems), meaning market and dispatch logic is more heavily claimed than the underlying grid control itself.
Filing growth compares 2021 (1 records) with 2024 (12) — a three-year span. 2024 is the most recent year we treat as complete: publication lags filing by roughly 18 months, so 2025 onwards are still filling in and any growth rate that ends there would understate the field. Top-5 share is the combined record count of the five largest assignees divided by all 44 records in scope (CR5), not by the ranked leaders only.
What this patent set covers
Virtual power plant (VPP) simulation and modeling patents describe how distributed energy resources — batteries, EV chargers, rooftop solar, demand-response loads — are aggregated, forecast and dispatched through a software layer that behaves like a single power plant to the grid. This landscape isolates filings that combine power system or market simulation with aggregation modeling or digital-twin techniques, rather than VPP hardware or grid-control patents generally. The scope is narrow by design: it captures the modeling and simulation layer specifically, which is where forecasting accuracy, market-clearing logic and digital-twin fidelity get contested.
Coverage runs from 2015 through the 2026 data cut-off, though recent-year counts are understated because publication typically lags filing by around 18 months. Even with that lag built in, the shape of the curve — near-zero activity through 2022, then a sharp climb — is unusually late and steep for a smart-grid sub-field.
Filing trend and technology composition
Two views of the same 44-family dataset: when the filings happened, and which technical classes they touch.
A late, steep ramp
Filings sat at zero in 2017 and had reached only 1 by the 2022 midpoint. The climb to 23 in the peak year shows the field accelerating rather than maturing — most of the claim space was staked out in the last few years, which means freedom-to-operate analysis needs to weight recent filings heavily rather than relying on older, more-cited records.
Business logic leads, grid hardware follows
G06Q (business, commerce and administrative data processing) touches 38 of 44 records, ahead of H02J (power supply and grid systems) at 28 and G06N (AI-based computing) at 20. Smaller counts in B60L, G06T, G05B and G01R mark adjacent branches — EV propulsion integration, visualization, control-loop specifics and measurement — that are present but thin.
Shares are the percentage of the 44 records in scope. A patent can carry several IPC classes, so the shares add up to more than 100%.
Go deeper on Virtual Power Plant Simulation and Modeling with Eureka
This page is one run against one query. Ask Eureka your own question about virtual power plant simulation and modeling and every answer comes back with the patent numbers behind it.
Try EurekaThe most-cited records
ML-optimized VPP controller for battery-powered EV charging networks (US20250079836A1)
Filed by Banpu Innovation & Ventures LLC, this patent describes a VPP controller that manages an EV charging station, a battery storage system and an independent power plant together. It trains a machine-learning model to predict the independent power plant's output over a forecast horizon, then reconciles that prediction against charging demand and available power from the grid, battery and plant to decide dispatch in real time.One of the few US-filed records in the set and the highest-cited non-Chinese filing.
| # | Publication no. | Patent title | Citations |
|---|---|---|---|
| 1 | CN115954933A | 电网数字孪生系统构建方法、装置、电子设备和存储介质 | 25 |
| 2 | CN114169856A | 一种综合能源协同管控系统 | 12 |
| 3 | CN120409220A | 一种融合数字孪生与强化学习的虚拟电厂绿能消纳协同方法及系统 | 5 |
| 4 | US20250079836A1 | ML-optimized VPP controller for battery powered ev charging networks | 5 |
| 5 | CN120879809A | 一种实现新能源消纳的虚拟电厂调控方法及系统 | 4 |
| 6 | CN120638336A | 基于数字孪生的虚拟电厂智能调度方法及系统 | 4 |
| 7 | CN120150262A | 基于数字孪生的虚拟电厂多层级协同优化控制方法 | 4 |
| 8 | CN121097697A | 一种虚拟电厂综合管理系统 | 3 |
| 9 | CN119918869A | 一种虚拟电厂行为特征个性化预测方法及系统 | 3 |
| 10 | CN120450339A | 基于交能融合大模型的移动虚拟电厂动态协同优化方法 | 2 |
Citation counts favor older filings simply because they've had more time to accumulate references inside the searched corpus — read them as markers of influence, not of current technical importance.
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. Each row carries its publication number; clicking a row searches Eureka by that number.
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Four read-throughs from the filing trend, technology mix and citation pattern above.
The field is compounding, not plateauing
A midpoint of just 1 family in 2022 followed by a peak of 23 shows most of the technical positions in this dataset were staked within the last few filing years. Anyone benchmarking against 2020-era filings is looking at a nearly empty field.
Prior art risk is not evenly distributed
South Korea and the United States each account for only 3 records. A search or clearance exercise that skips Chinese-language filings will miss the majority of the relevant art in this specific niche.
Business and AI logic sit on top of thinner grid claims
The three leading subclasses overlap heavily inside individual filings, meaning many patents claim the market/dispatch logic and the underlying grid interaction together. Isolated hardware-only claims in H02J without the business layer are less common.
Collaboration is thin and utility-led
Co-assignee activity centers on a state grid operator and its research institute, with single-count pairings to regional supply bureaus. There is no dense cross-company R&D cluster yet — collaboration filings are the exception, not the norm.
Eureka can read the same corpus for gaps instead of for coverage: under-claimed branches adjacent to virtual power plant simulation and modeling, with the prior art for and against each one.
Who is filing, and where the gaps are
Assignee activity is led by Chinese state-grid entities and research institutes, with momentum recently shifting toward newer, smaller filers even as established players show flat or declining recent-year counts.
New entrants are picking up where incumbents paused
While the largest historical filer shows a -100% YoY drop to zero in the latest year, a smaller institutional filer posted 2 filings in the same period — a sign the field's center of gravity may be shifting away from the earliest movers.
Several early leaders went quiet in the latest year
State Grid Corporation of China, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences and China Electric Power Research Institute Co., Ltd. all show 0 filings in the latest year after prior activity. This could reflect a genuine pause, a publication-lag gap, or a strategic shift to adjacent filing categories not captured by this search string.
State grid and its research arm anchor the collaboration graph
State Grid Corporation of China and China Electric Power Research Institute Co., Ltd. form the only pair with more than one joint filing; the remaining co-assignee pairs are single instances involving regional supply-company subsidiaries.
| Assignee | Recent year | YoY |
|---|---|---|
| Jiangsu Business and Trade Vocational College | 2 | — |
| State Grid Corporation of China | 0 | -100% |
| Hunan University Industry-Academia Cooperation Group | 0 | — |
| State Grid Henan Electric Power Company | 0 | — |
| Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences | 0 | -100% |
| China Electric Power Research Institute Co., Ltd. | 0 | -100% |
| BANPU INNOVATION & VENTURES LLC | 0 | — |
| Chongqing Sanxia Water Conservancy and Electric Power (Group) Co., Ltd. | 0 | -100% |
Where to take this
The trend and composition data point to a field still being staked out. Two practical next steps follow from that.
Run a freedom-to-operate check weighted toward 2023-2026 filings
Because the peak year sits at 23 families against a 2022 midpoint of just 1, older art is a poor proxy for current claim density. Any clearance search should weight the last two to three filing years heavily and treat the current year's count as a floor, not a ceiling.
Explore filings in EurekaPrioritize Chinese-language prior art in any search strategy
With 38 of 44 records filed via China's receiving office, an English-only search of this niche will systematically undercount the relevant art. Machine-translated full-text search against Chinese filings is not optional here.
Search full-text in EurekaCommon questions about this landscape
In this landscape, it means a filing that combines power-system or market simulation techniques with aggregation modeling or digital-twin methods for distributed energy resources — not VPP hardware patents generally, and not grid-control patents that lack a simulation or modeling claim. The search string specifically requires both an aggregation/VPP term and a simulation or digital-twin term in the title or claims. This narrows the set to the software layer that forecasts, models and clears markets for aggregated DERs, rather than the physical equipment or basic grid-control logic underneath it.
Filing activity in this dataset is led by Chinese state-grid entities and affiliated research institutes, with the strongest collaboration pair being a state grid operator and its power science research institute. Momentum has recently shifted, though: several early leaders show zero filings in the latest year, while smaller institutional filers have picked up activity. This suggests the leaderboard is not settled and could look different within a year or two of additional publications.
The dataset shows near-zero activity through 2022 followed by a sharp climb to a peak of 23 families, which tracks the broader push toward grid-scale renewable integration and distributed-energy aggregation that intensified in the early 2020s. Digital-twin and AI-forecasting techniques also only became mature and patentable in combination with VPP dispatch logic around this period. Because publication lags filing by roughly 18 months, the most recent year's count is understated, and the true inflection point may be even sharper than the raw numbers show.
Smaller IPC branches in this dataset — B60L (EV propulsion integration), G06T (digital-twin visualization), G05B (closed-loop control tuning) and G01R (measurement feedback) — each appear in only one to three records versus 38 for the dominant business-logic class. That gap suggests EV-fleet-specific dispatch modeling, visualization layers for digital twins, and fine-grained control-loop tuning for aggregated DERs are touched by existing filings but not densely claimed. A first-filer with a specific technical implementation in one of these branches has more room to establish a defensible position than in the crowded business-logic and grid-interaction space.
No — dense filing in a subclass indicates that claim space is occupied, not that the underlying technology is settled or proven at commercial scale. In this dataset, the filing curve is still accelerating rather than leveling off, and the field's single most-cited AI/EV-charging patent was only published in 2025. High claim density here is better read as a signal of active competition for a still-forming technical direction, not as evidence that the modeling approaches involved are technically mature or de-risked.
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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.