IP Library Granted Patent US 12,632,802
Granted Patent B2
US 12,632,802 · App. 18/001,412 · Granted May 19, 2026

Method and system for resource management

Inventors: Sourav Dutta (Dublin, IE); Andrei Marinescu (Dublin, IE); Leonard Feehan (Birr, Co. Offaly, IE); Manoj Gokhale (Pune, IN); Eugene Ryan (Dublin, IE)
Assignee: EATON INTELLIGENT POWER LIMITED
G06Q10/04G05B19/042G06Q50/06G05B2219/2639
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Quick Facts
Patent No.
US 12,632,802
App. No.
18/001,412
Granted
May 19, 2026
Kind
B2
Abstract

A method of resource management for transferring resources from providers to consumers is described. The method comprises the following steps. Supply parameters for the providers and demand parameters for the consumers are established, and constraints on the allocation of the resources are also established, as is an optimisation function for determining matches between providers and consumers. The optimisation function is solved for the established constraints using a constraint-based problem solver to determine matches between providers and consumers. Resources are then transferred from providers to consumers according to the determined matches. A computing system adapted to perform this method is also described, along with a power distribution system including such a computing system.

Claims (36)

1 . A method of resource management for transferring electrical power from providers to consumers, wherein the providers are power sources and the consumers are loads, the method comprising:

establishing supply parameters for the providers and demand parameters for the consumers, wherein the supply parameters and the demand parameters comprise quantity of power;

establishing constraints on the allocation of electrical power;

establishing an optimisation function for determining matches between providers and consumers;

determining optimal values for the supply parameters and the demand parameters without the constraints:

after determining the optimal values, solving the optimisation function for the constraints using a constraint-based problem solver to determine matches between providers and consumers; and

transferring electrical power from the providers to the consumers according to the determined matches between the providers and the consumers.

2 . The method of claim 1 , further comprising validating the supply parameters and the demand parameters after they are established.

3 . The method of claim 1 , wherein solving the optimisation function is a linear programming problem.

4 . The method of claim 1 , wherein the method is performed for a plurality of time slots, wherein at least the steps of establishing the supply parameters and the demand parameters, establishing the optimisation function, solving the optimisation function and transferring resources are repeated for each time slot.

5 . The method of claim 4 , wherein different optimisation functions are used for at least some of the time slots.

6 . The method of claim 1 , wherein a party may be either a power producer or a power consumer at different times.

7 . The method of claim 1 , wherein the supply parameters and the demand parameters comprise a quantity of power.

8 . The method of claim 7 , wherein the supply parameters and the demand parameters comprise cost of power.

9 . The method of claim 1 , wherein the constraints comprise systemic restraints for a power grid.

10 . The method of claim 1 , wherein the constraints comprise limitations placed by a provider of the providers or a consumer of the consumers.

11 . The method of claim 1 , further comprising making a record of transferring of the electric power from producers to consumers and storing the record in a secure storage.

12 . The method of claim 11 , wherein the secure storage is a blockchain.

13 . The method of claim 1 , wherein the optimal values are determined by assuming that at least one power source of the power sources has unlimited supply and that the loads have no resilience restraint and wherein the optimisation function is solved to find matches as close as possible to the optimal values.

14 . A computing system comprising a processor and a memory and programmed to perform as a platform for allocating electrical power from providers to consumers, wherein the providers are power sources and the consumers are loads, the computing system configured to:

receive and store supply parameters for the providers, demand parameters for the consumers, and constraints on allocation of the electric power, wherein the supply parameters and the demand parameters comprise quantity of power;

establish an optimisation function for determining matches between providers and consumers;

establish optimal values for the supply parameters and the demand parameters without the constraints;

after establishing the optimal values, solve the optimisation function for the constraints to determine matches between providers and consumers; and

distribute electrical power over a power grid between producers and consumers according to the determined matches between the providers and the consumers.

15 . The computing system of claim 14 , further adapted to determine the constraints on the allocation of the electric power from received provider information and received consumer information.

16 . The computing system of claim 14 , wherein the computing system is further configured to validate the supply parameters and the demand parameters after they are established.

17 . The computing system of claim 14 , wherein solving the optimisation function is a linear programming problem and wherein the linear programming problem is solved by a linear programming problem solver.

18 . The computing system of claim 14 , wherein the computing system is adapted to allocate resources for a plurality of time slots, wherein at least establishing the supply parameters and the demand parameters, establishing the optimisation function and solving the optimisation function are repeated for each time slot.

19 . The computing system of claim 18 , wherein the computing system is further configured establish the optimisation function is adapted to establish different optimisation functions for different time slots.

20 . The computing system of claim 14 , wherein the computing system is a power distribution platform.

21 . A power distribution system comprising a power distribution platform as claimed in claim 20 .

22 . The power distribution system of claim 21 , wherein the constraints comprise systemic restraints for a power grid.

23 . The computing system of claim 14 , wherein the supply parameters and the demand parameters comprise a quantity of power and cost of power.

24 . The computing system of claim 14 , wherein the constraints comprise limitations provided by a provider or a consumer.

25 . The computing system of claim 14 , wherein the computing system includes a constraint-based problem solver to solve the optimisation function.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Apr 8, 2026
From: DUTTA, SOURAV; MARINESCU, ANDREI; FEEHAN, LEONARD; GOKHALE, MANOJ; RYAN, EUGENE
To: EATON INTELLIGENT POWER LIMITED
Reel/Frame 074303/0546 →
Priority Claims (2)
IN 202011024409 · Jun 10, 2020 · national
GB 2012188 · Aug 5, 2020 · national
Continuity (1)
Related Publication 20230222400A1 · Jul 13, 2023
References Cited (13)
US 10340735B2 · Yoo · 2019 [cited by examiner]
US 10853750B2 · Daniel · 2020 [cited by examiner]
US 11689613B2 · Dailianas · 2023 [cited by examiner]
US 20180299852A1 · Orsini · 2018 [cited by applicant]
CN 103956919A · 2014 [cited by examiner]
CN 107769595A · 2018 [cited by examiner]
CN 116632914A · 2023 [cited by examiner]
WO WO2012115966A2 · 2012 [cited by examiner]
WO 2019070357A1 · 2019 [cited by applicant]
WO 2019084262A1 · 2019 [cited by applicant]
Karla Kvaternik, et al., “Privacy-Preserving Platform for Transactive Energy Systems”, arxiv.org, Cornell University Library, 201 Olin Library Cornell University Ithaca, NY 14853, Sep. 27, 2017 (Sep. 27, 2017), XP080824… [cited by applicant]
CNIPA, Office Action issued Jul. 5, 2025 in corresponding Chinese Application No. CN 202080101930.X. [cited by applicant]
CNIPA, Office Action issued Sep. 9, 2025 in corresponding Chinese Application No. CN 202080101930.X. [cited by applicant]