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Run your analysis now →https://eureka.patsnap.com/resources/blog/rd-blog/demand-response-load-forecasting-machine-learning-algorithm-patent-landscape/ · Patsnap · data cut-off 2026-10-20 · downloaded from the live page
Patent Landscape · Patent Landscape SnapshotDemand Response Load Forecasting Machine Learning Patents
18 patent families cover demand response load forecasting with ML; filings sit with 19 listed entities and no single leader.
22
Published Records
18
Simple Patent Families
9%
In Force at Cut-off
IN
Leading Jurisdiction
22 published records collapse into 18 simple (DOCDB) families; the difference is the same invention filed in more than one country. In force = 2 of 22 records still granted and maintained at the data cut-off; the rest are pending, withdrawn, refused or lapsed.
- 18 simple patent families and 22 published records make up this search, with 19 filers sharing the top count of 1 family each, no single filer leads.
- India received 17 of the 22 published records the largest share of any receiving office in this set, ahead of the United States at 2.
- G06Q and H02J each appear on 14 of the 18 families a 77.8% share apiece, the two technology classes most present in this dataset.
Published byPatsnap Research··6 min readSourced from Patsnap Eureka
Overview
What this search covers
This landscape is built from the search string TAC:(("demand response" AND "load forecasting") AND ("machine learning" OR "neural network*")), matched against titles, abstracts and claims. It returns 18 simple patent families and 22 published records, with no date limit applied, so every matching record the search engine can find is in scope regardless of when it was filed.
This is a small pool: 18 families and 19 listed filers. The figures below are a starting point for a closer manual search, not a complete map of this technology area.
Records vs. families in scope
Ordered by volume only, not by importance or claim strength. Counted in simple (DOCDB) patent families, so one invention filed in several countries counts once. Names come from Patsnap's standardised assignee field as recorded on each document; subsidiaries and group companies are not merged. The icon before each name is read from the name itself (words such as University, Institute or Ltd); the data carries no organisation-type field, so treat it as a reading aid rather than a classification. 2 rows in this table share the name GRID (State Grid Electric Power Research Institute Wuhan Energy Efficiency Evaluation Co., Ltd., STATE GRID TIANJIN ELECTRIC POWER COMPANY). They are left as separate rows, so the largest-filer figure above is per legal entity, not per group. Rows that look related still cannot be added together: one family can name several of them. Counted one by one, those rows between them cover more than the largest single row does, so the largest single row is not necessarily the largest filer in this field. How much those rows cover together is not something this dataset can say: one family can name several of them, so their counts cannot be added. Every ranking statement on this page is per individual filer row, never per group. Filings held by named individuals rather than organisations are removed where they can be identified (43 here); that identification is not exhaustive, so an individually held filing can still appear below. Either way those filings stay inside the totals above. This table shows the top 19 of the 19 filers returned for this search; the data endpoint returns at most 100 entities, so even that 19 is not the complete set of filers. A single family can name more than one filer, so these counts overlap and do not add up to the total.
Source: Patsnap Eureka. Assignee ranking and totals. Derived from one Patsnap search for Demand Response Load Forecasting Machine Learning Algorithm Patent Landscape, covering all matching records regardless of filing date (the search string sets no date limit), retrieved 2026-10-20. Counts cover published records only and move as new filings publish.Run this in Eureka MCP
The Numbers
Filings, filers and classification mix
Three views of the same 18 families: where documents were filed, who filed them, and which IPC subclasses they carry.
Filing trend by earliest filing year (published records)
Records run from 2012 to 2026, with a peak so far of 9 in 2025. 2022 onward is still filling in as later filings publish, so the last few years understate the eventual count and should not be read as a slowdown or a rise.
Counted in published records by earliest filing year, not de-duplicated into families. A filing is counted in the year it was filed, but it only becomes visible after it publishes: roughly 18 months for most routes, and up to 30 months where a PCT application enters national phase. 2022 onwards are therefore still filling in and are shaded; no growth figure on this page uses them. Because this series counts documents rather than inventions, a rise can mean more inventions or the same inventions filed in more countries; this dataset cannot separate the two.
IPC subclass composition (share of 18 families)
G06Q and H02J each sit on 14 of the 18 families (77.8%), and G06N on 9 (50.0%). Because a family can carry several IPC classes, these shares add up to more than 100%.
Shares are the percentage of the 18 patent families in scope. One patent family can carry several IPC classes, so the shares add up to more than 100%.
Source: Patsnap Eureka. Filing trend and technology composition. Derived from one Patsnap search for Demand Response Load Forecasting Machine Learning Algorithm Patent Landscape, covering all matching records regardless of filing date (the search string sets no date limit), retrieved 2026-10-20. Counts cover published records only and move as new filings publish.
Go deeper on Demand Response Load Forecasting Machine Learning Algorithm Patent Landscape with Eureka
This page is one run against one query. Ask Eureka your own question about demand response load forecasting machine learning algorithm patent landscape and every answer comes back with the patent numbers behind it.
Try EurekaRepresentative Filing
A record from the result set
From the Result Set
Load forecasting from individual customer to system level based on price
AUTOGRID SYSTEMS, INC.
The present invention relates to system and method for providing near real-time DR events and price signals to the customer end-points to optimally manage the available DR resources. The system utilizes bottom up load forecasting for accurate individualized forecasts for customer loads in the presence of dynamic pricing signals. For better efficiency and reliability of grid operation the system utilizes advanced machine learning and robust optimization techniques for real-time and 'personalized' DR-offer dispatch.This is the first record returned under the database's default ordering, not a ranking by importance or citations. What its granted claims actually require has to be read from the claim set itself, an abstract and a family count cannot establish that.
Selected as the first record the search returns under the database default order, then shown in full. It is not ranked by citations, claim breadth or commercial importance, and it is not a judgement about which filing in this space matters most.
Source: Patsnap Eureka. The first record the search returned, shown in full. Derived from one Patsnap search for Demand Response Load Forecasting Machine Learning Algorithm Patent Landscape, covering all matching records regardless of filing date (the search string sets no date limit), retrieved 2026-10-20. Counts cover published records only and move as new filings publish.Run this in Eureka MCP
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Reading the dataset
These cards report figures directly from the search results. None of them should be read as a ranking of quality or strategy.
Scope
18 families / 22 records
Simple patent families vs. published records
Two different counts, same search
The search returns 18 simple patent families and 22 published records. A family groups one invention across countries; a record counts each publication separately, so the two numbers measure different things and are not interchangeable.
No date limit was applied to this search.
Filer spread
19 filers at 1 family each
Top count shared by 19 listed entities
No single filer leads the count
19 of the 19 listed filers are named on 1 simple patent family each, apart from the largest row. Filer rows are not summed here because one family can name more than one filer, and the listed rows already total 19 against 18 families.
Individuals filing in their own name are excluded from this list but remain in the totals.
Legal status
2 of 22 in force
Granted and in force at retrieval
A small share were in force at the retrieval date
2 of the 22 published records (9%) were granted and in force when the data was retrieved on 2026-10-20. Legal status changes continuously and is not a measure of a filing's quality or commercial value.
Other statuses are not broken out in this dataset.
Filing location
India: 17 of 22 records
Largest receiving office by published records
Where applications were filed, not where filers are based
Of 5 receiving offices returned, India accounts for 17 of 22 published records, followed by the United States at 2. This describes filing location only; the dataset gives no information about any filer's nationality or location.
All 5 receiving offices returned by the search are counted here.
Eureka AI Agent
Looking for what nobody has claimed yet?
Eureka can read the same corpus for gaps instead of for coverage: under-claimed branches adjacent to demand response load forecasting machine learning algorithm patent landscape, with the prior art for and against each one.
Source: Patsnap Eureka. Derived observations on the same dataset. Derived from one Patsnap search for Demand Response Load Forecasting Machine Learning Algorithm Patent Landscape, covering all matching records regardless of filing date (the search string sets no date limit), retrieved 2026-10-20. Counts cover published records only and move as new filings publish.Run this in Eureka MCP
Next Steps
Taking this further
This page surfaces the figures a first search returns. Narrowing or widening the terms, or reading specific claim sets, is the next step for any of the questions above.
Pull the granted claims that matter
Family counts and abstracts cannot establish claim scope. Where a specific filing looks relevant, read its granted claims directly before drawing any conclusion about what it covers.
Open Eureka →Re-run with adjacent terms
A small pool like this one is sensitive to the exact search string used. Broadening or substituting terms such as 'load prediction' or 'grid forecasting' may surface records this search did not catch.
Explore in Eureka →Source: Patsnap Eureka. Suggested next steps. No new data: every figure named here is one of those above. Derived from one Patsnap search for Demand Response Load Forecasting Machine Learning Algorithm Patent Landscape, covering all matching records regardless of filing date (the search string sets no date limit), retrieved 2026-10-20. Counts cover published records only and move as new filings publish.Run this in Eureka MCP
FAQ
Common questions
This specific search returns 18 simple patent families and 22 published records, with no date limit applied. That count depends entirely on the search string used, TAC:(("demand response" AND "load forecasting") AND ("machine learning" OR "neural network*")), and a differently worded search could return a different set. Treat this as one search's result, not an authoritative total for the technology area.
There is no single leading filer in this dataset: 19 listed entities are each named on 1 simple patent family, with the largest row, JAI NARAIN COLLEGE OF TECHNOLOGY, at 1 of 18 families (5.6%). Filer rows cannot be added together to produce a combined share, because a family can name more than one filer and the listed rows already sum to more than the family total. Names are also not rolled up to corporate group, so related-looking entries are counted and shown separately.
Within the 18 families in scope, G06Q (business, commerce and admin data processing) and H02J (power supply and grid systems) each appear on 14 families (77.8%), and G06N (AI-model computing) appears on 9 (50.0%). H04L (digital information transmission) appears on 4 families (22.2%). Because one family can carry several IPC classes, these shares add up to more than 100%, and they describe classification overlap rather than four separate groups of documents.
2 of the 22 published records (9%) were granted and in force at the data retrieval date of 2026-10-20. The remaining records fall into other statuses such as pending, withdrawn, refused or lapsed, but this dataset does not break those out individually. In-force status reflects a snapshot at one point in time and changes continuously, so it should not be read as a measure of a filing's quality or value.
The search returned 5 receiving offices in total: India (17 published records), the United States (2), China (1), the European Patent Office (1) and WIPO under the PCT (1). These figures describe where applications were filed, not where any filer is based, since this dataset carries no nationality or location information about the filers themselves. A record can also appear more than once across offices if the same invention was filed in multiple places.
The published-records trend runs from 2012 through 2026, with a peak so far of 9 records in 2025. Records from 2022 onward are still filling in as later filings publish, most recent filings take 18 to 30 months to become visible, so the final 2-4 years understate their eventual totals. For that reason, the recent-year figures should not be read as a decline, a plateau, or an acceleration.
Answers are grounded in the same dataset. Derived from one Patsnap search for Demand Response Load Forecasting Machine Learning Algorithm Patent Landscape, covering all matching records regardless of filing date (the search string sets no date limit), retrieved 2026-10-20. Counts cover published records only and move as new filings publish.Run this in Eureka MCP
Research Demand Response Load Forecasting Machine Learning Algorithm Patent Landscape in depth with Eureka
Go past this page: query the whole demand response load forecasting machine learning algorithm patent landscape corpus yourself, in your own scope.
Every answer comes back with patent numbers you can open.
How this page was built, and what the numbers do and do not mean
Search. Every figure on this page comes from one Patsnap search, run once and not edited afterwards. This is the exact search string:
TAC:(("demand response" AND "load forecasting") AND ("machine learning" OR "neural network*"))Reading the field codes: TAC searches the title, abstract and claims of each record, not the full description. The search string sets no date limit, so the scope is every matching record in the database regardless of when it was filed. It is not restricted to recent years. How this string was built matters for how far the counts can be pushed. It was generated in batch from a topic list rather than hand-crafted for this page, and the result set is not manually screened. A keyword search over title, abstract and claims both over-captures (unrelated filings that happen to use the same words) and under-captures (the same invention written in different words). This page cannot measure either effect, so read every figure here as what this particular string returned, not as what exists in the field. One subclass (G06Q) carries 77.8% of the patent families, so this search returned a classification-tight set.
What is being counted. Two different units appear on this page and they are not interchangeable. The filer list and the technology split are counted in simple (DOCDB) patent families: one invention counts once however many countries it was filed in. The total, the jurisdiction split and the filing-year chart are counted in published records: the same invention counts once per publication. For this search that is 22 records and 18 families. Record counts reward filing in many jurisdictions; family counts do not. Shares are only ever taken against a denominator in the same unit, and each one names it.
Who the filers are. Names come from Patsnap's standardised assignee field, as recorded on the documents themselves. They are not rolled up to corporate group: a parent and its subsidiaries appear as separate entries, and a portfolio acquired from another company stays under the name on the document unless the assignment is reflected there. This list is meant to carry organisations, not people. Filings held by a named individual are identified by matching the assignee against the inventors on the same search, and, for names written in Chinese, Japanese or Korean characters, by the name carrying no organisational suffix; those are removed from the list (43 of them here). Neither test is exhaustive: the inventor list it matches against is itself capped, and a personal name written in Latin script with no organisational wording in it cannot be told apart from a short company name by rule. So an individually held filing can still appear in the list. Those filings stay inside every total and share on this page either way, so the listed entries can add up to less than the total. A record shown in full further down still names its assignee exactly as the patent office records it, including where that is a person: that name is how the record is identified and checked. What is left out of the ranking is people as ranked entries, not people as cited sources. The table shows the top 19 of the 19 filers returned, ordered by count alone; the data endpoint returns at most 100 entities, so even that 19 is not every filer. One patent family can name several filers and each is counted separately, so these rows are not slices of a divided whole: adding them together over-counts, and this page deliberately publishes no combined "top five" share for that reason. See every filer, individuals included
Dates. The year chart counts by earliest filing year, not publication year. A filing only becomes visible once it publishes: roughly 18 months for most routes, and up to 30 months where a PCT application enters national phase. Measured across these pages, the year four back from today still holds only about 89% of its eventual count. 2022 onwards are therefore shaded on the chart as still filling in. The data behind this page was retrieved on 2026-10-20.
Legal status. "In force" counts documents whose legal status at retrieval was granted and maintained (2 of 22). Everything else is pending, withdrawn, refused, lapsed or not determinable, and those states are not broken out here because the underlying codes do not separate them cleanly. Legal status changes continuously and is reported per document, not per family. Get the status breakdown in Eureka
Classification. The technology split uses IPC subclasses (four characters, for example H01M). A single record usually carries several, so the shares add up to more than 100% and a record can appear in more than one bar. Subclass is a coarse grouping; it describes the field a record was classified into, not what the claims cover. Break the classes down to subgroup level
Who wrote the words. The tables, charts, counts, shares and patent numbers on this page are produced directly from the search result by a program; none of them are written or estimated by a language model. The surrounding prose, headings, FAQ answers and the answers in the question panel are drafted by a language model that is given those same figures and is not permitted to introduce others. Prose can still mis-describe a correct figure, so where the two disagree, the tables and charts are the record.
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 limitations that apply to every figure above. Recent filings are under-counted, because an application is not public until roughly 18 months after filing and database loading adds further delay. The search string defines and constrains everything shown: records that use different terminology, or that sit outside the fields searched, are absent and cannot be counted. Applicant names, classification codes, legal-status codes and citation records are taken as recorded and may contain errors, duplicates, omissions or stale entries. Ordering by volume is not a measure of quality, scope, enforceability or commercial value, and a larger portfolio is not a stronger one. 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, validity or infringement search, nor does it constitute legal, financial, investment, or professional advice, and it should not be relied upon as such. No attorney-client relationship is created by it. Any patent, commercial, or strategic decision should be verified independently against the primary records 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.
The question panel. The answers behind the suggested questions on this page were written when the page was generated, not in response to your click. The progress steps that play before an answer appears are an animation of how that analysis was done; nothing is being searched or computed at that moment. Typing your own question instead opens Patsnap Eureka, which does run it live.
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.