IP Library Granted Patent US 12,609,035
Granted Patent B2
US 12,609,035 · App. 17/882,672 · Granted Apr 21, 2026

Grid-related event prediction

Inventors: Norman Lu (Fairview, TX); Maximilian Parness (Takoma Park, MD)
Assignees: TOYOTA MOTOR NORTH AMERICA, INC.; TOYOTA JIDOSHA KABUSHIKI KAISHA
G08G1/202B60L58/13G06Q30/0205G06Q50/06B60L2240/62
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Quick Facts
Patent No.
US 12,609,035
App. No.
17/882,672
Granted
Apr 21, 2026
Kind
B2
Abstract

An example operation includes one or more of determining an issue exists with a resource delivery to an electricity provider, determining an electric impact, based on the issue, determining an area that will be affected by the electric impact, and dispatching vehicles to provide electricity to locations within the area.

Claims (79)

1 . A method performed by a processor, the method comprising:

analyzing an impact on an electric grid caused by a resource delivery issue;

identifying an area affected by the impact;

dispatching vehicles to provide electricity to locations within the area; and

controlling the vehicles at the locations to perform a vehicle-to-grid (V2G) transfer of energy to the electric grid;

monitoring a state of charge of each dispatched vehicle in real-time during the transfer;

dynamically adjusting an amount of energy transferred from each vehicle based on grid demand, vehicle constraints, and energy reserve thresholds; and

ensuring that each vehicle retains a minimum charge level required for one or more returning to its base location or fulfilling subsequent tasks.

2 . The method of claim 1 , wherein the identifying the issue with the delivery of the resource comprises:

receiving a notification from a provider of the resource of a limited resource supply;

comparing a current level of the resource to a threshold; and

notifying the electricity provider in response to the current level of the resource being below the threshold.

3 . The method of claim 1 , wherein the analyzing the impact comprises:

predicting the issue with the delivery of the resource will exist for a time period;

estimating an electrical demand during the time period; and

calculating a difference between the issue with the resource and the electrical demand.

4 . The method of claim 1 , wherein the identifying the area comprises:

retrieving a geographical area serviced by the electricity provider; and

designating a portion of the geographical area as the area based on electricity lost in the portion of the geographical area.

5 . The method of claim 1 , wherein the dispatching the vehicles to provide electricity comprises:

identifying vehicles proximate to the area;

selecting a subset of the vehicles equipped with V2G capabilities and sufficient electricity storage;

transmitting instructions to the subset of the vehicles to proceed to the locations within the area; and

coordinating a V2G energy transfer between the subset of vehicles and grid infrastructure in the area to provide electricity to the locations within the area.

6 . The method of claim 1 , comprising:

selecting vehicles having an available electricity amount above a first threshold and a vehicle availability above a second threshold; and

dispatching the selected vehicles to provide electricity to locations within the area.

7 . A system, comprising:

a processor that, when executing instructions stored in a memory, is configured to:

analyze an impact on an electric grid caused by a resource delivery issue;

identify an area affected by the impact;

dispatch vehicles to provide electricity to locations within the area; and

control the vehicles at the locations to perform a vehicle-to-grid (V2G) transfer of energy to the electric grid;

monitor a state of charge of each dispatched vehicle in real-time during the transfer;

dynamically adjust an amount of energy transferred from each vehicle based on grid demand, vehicle constraints, and energy reserve thresholds; and

ensure that each vehicle retains a minimum charge level required for one or more returning to its base location or fulfilling subsequent tasks.

8 . The system of claim 7 , wherein when the processor identifies the issue with the delivery of the resource, the processor is further configured to:

receive a notification from a provider of the resource of a limited resource supply;

compare a current level of the resource to a threshold; and

notify the electricity provider in response to the current level of the resource being below the threshold.

9 . The system of claim 7 , wherein when the processor analyzes the impact, the processor is further configured to:

predict the issue with the delivery of the resource will exist for an upcoming time period;

estimate an electrical demand during the time period; and

calculate a difference between the issue with the resource and the electrical demand.

10 . The system of claim 7 , wherein when the processor identifies the area, the processor is further configured to:

retrieve a geographical area serviced by the electricity provider; and

designate a portion of the geographical area as the area based on electricity lost in the portion of the geographical area.

11 . The system of claim 7 , wherein the processor dispatches the vehicles to provide electricity, the processor is further configured to:

identify vehicles proximate to the area;

select a subset of the vehicles equipped with V2G capabilities and sufficient electricity storage;

transmit instructions to the subset of the vehicles to proceed to the locations within the area; and

coordinate a V2G energy transfer between the subset of vehicles and grid infrastructure in the area to provide electricity to the locations within the area.

12 . The system of claim 7 , wherein the processor is configured to:

select vehicles that have an available electricity amount above a first threshold and a vehicle availability above a second threshold; and

dispatch the selected vehicles to provide electricity to locations within the area.

13 . A computer-readable storage medium comprising instructions that, when executed by a processor, cause the processor to perform:

analyzing an impact on an electric grid caused by a resource delivery issue;

identifying an area affected by the impact;

dispatching vehicles to provide electricity to locations within the area;

controlling the vehicles at the locations to perform a vehicle-to-grid (V2G) transfer of energy to the electric grid;

monitoring a state of charge of each dispatched vehicle in real-time during the transfer;

dynamically adjusting an amount of energy transferred from each vehicle based on grid demand, vehicle constraints, and energy reserve thresholds; and

ensuring that each vehicle retains a minimum charge level required for one or more returning to its base location or fulfilling subsequent tasks.

14 . The computer-readable storage medium of claim 13 , wherein the identifying the issue with the delivery of the resource comprises:

receiving a notification from a provider of the resource of a limited resource supply;

comparing a current level of the resource to a threshold; and

notifying the electricity provider in response to the current level of the resource being below the threshold.

15 . The computer-readable storage medium of claim 13 , wherein the analyzing the impact comprises:

predicting the issue with the delivery of the resource will exist for an upcoming time period;

estimating an electrical demand during the time period; and

calculating a difference between the issue with the resource and the electrical demand.

16 . The computer-readable storage medium of claim 13 , wherein the identifying the area comprises:

retrieving a geographical area serviced by the electricity provider; and

designating a portion of the geographical area as the area based on electricity lost in the portion of the geographical area.

17 . The computer-readable storage medium of claim 13 , wherein dispatching the vehicles to provide electricity comprises:

identifying vehicles proximate to the area;

selecting a subset of the vehicles equipped with V2G capabilities and sufficient electricity storage;

transmitting instructions to the subset of the vehicles to proceed to the locations within the area; and

coordinating a V2G energy transfer between the subset of vehicles and grid infrastructure in the area to provide electricity to the locations within the area.

Assignments (2)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Aug 19, 2026
From: TOYOTA JIDOSHA KABUSHIKI KAISHA
To: TOYOTA MOTOR NORTH AMERICA, INC.
Reel/Frame 075707/0445 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Aug 8, 2022
From: LU, NORMAN; PARNESS, MAXIMILIAN
To: TOYOTA MOTOR NORTH AMERICA, INC.; TOYOTA JIDOSHA KABUSHIKI KAISHA
Reel/Frame 060740/0386 →
Continuity (1)
Related Publication 20240046797A1 · Feb 8, 2024
References Cited (46)
US 7795756B2 · Brown · 2010 [cited by examiner]
US 7844370B2 · Pollack et al. · 2010 [cited by applicant]
US 8587260B2 · Kumar · 2013 [cited by applicant]
US 8810192B2 · Bridges et al. · 2014 [cited by applicant]
US 8872379B2 · Ruiz et al. · 2014 [cited by applicant]
US 9026347B2 · Gadh et al. · 2015 [cited by applicant]
US 9043038B2 · Kempton · 2015 [cited by applicant]
US 9400990B2 · Genschel et al. · 2016 [cited by applicant]
US 9511676B2 · Loftus et al. · 2016 [cited by applicant]
US 9634508B2 · Kearns et al. · 2017 [cited by applicant]
US 10203701B2 · Kurdi · 2019 [cited by examiner]
US 10279698B2 · Bridges et al. · 2019 [cited by applicant]
US 10320923B2 · Moghe et al. · 2019 [cited by applicant]
US 10647209B2 · Haas · 2020 [cited by examiner]
US 10850625B2 · Lowenthal · 2020 [cited by examiner]
US 12016707B2 · Haley · 2024 [cited by examiner]
US 12184803B2 · Horelik · 2024 [cited by examiner]
US 20040158360A1 · Garland, II · 2004 [cited by examiner]
US 20090210357A1 · Pudar · 2009 [cited by examiner]
US 20090222143A1 · Kempton · 2009 [cited by examiner]
US 20110172837A1 · Forbes, Jr. · 2011 [cited by examiner]
US 20110202418A1 · Kempton · 2011 [cited by examiner]
US 20120046798A1 · Orthlieb et al. · 2012 [cited by applicant]
US 20150365383A1 · De Groot · 2015 [cited by examiner]
US 20160159239A1 · Shi · 2016 [cited by examiner]
US 20170140603A1 · Ricci · 2017 [cited by examiner]
US 20180096628A1 · Fairchild et al. · 2018 [cited by applicant]
US 20190130763A1 · Kawasaki · 2019 [cited by examiner]
US 20190132719A1 · Mizutani · 2019 [cited by examiner]
US 20190349794A1 · Tavares Coutinho · 2019 [cited by examiner]
US 20200346751A1 · Horelik · 2020 [cited by examiner]
US 20210287549A1 · Nishida · 2021 [cited by examiner]
US 20210287550A1 · Mori · 2021 [cited by examiner]
US 20210335123A1 · Trundle · 2021 [cited by examiner]
US 20220171386A1 · Cui · 2022 [cited by examiner]
US 20220396174A1 · Nagata · 2022 [cited by examiner]
US 20230108953A1 · Kreiner · 2023 [cited by examiner]
US 20230115083A1 · Slutzky · 2023 [cited by examiner]
US 20240034180A1 · Bhimani · 2024 [cited by examiner]
CN 102164772A · 2011 [cited by applicant]
KR 101800909B1 · 2017 [cited by applicant]
“Use of Mobile Engine Generators as Source of Back-up Power” Iwai et. al. (Year: 2009). [cited by examiner]
International Search Report and Written Opinion issued in the International Application No. PCT/US2023/029793, mailed on Dec. 11, 2023. [cited by applicant]
Iwai et al., “Use of mobile engine generators as source of back-up power,” INTELEC 2009—31st International Telecommunications Energy Conference, Incheon, Korea (South), 2009, pp. 1-6, Retrieved from the internet entire … [cited by applicant]
Lei et al., “Mobile Emergency Generator Pre-Positioning and Real-Time Allocation for Resilient Response to Natural Disasters”, in IEEE Transactions on Smart Grid, vol. 9, No. 3, pp. 2030-2041, May 2018. [cited by applicant]
Malek et al., “Resilience Based Decision Metrics for dispatching Mobile Emergency Truck Generators in Distribution System,” 2021 IEEE International Conference in Power Engineering Application (ICPEA), Malaysia, 2021, pp… [cited by applicant]