IP Library › Granted Patent US 12,266,938
Granted Patent B2
US 12,266,938 · App. 17/494,676 · Granted Apr 1, 2025

Dynamic energy management and cost optimization in local grids

Inventors: Richard Thomas Jones (Port Coquitlam, CA); Christopher Stanley James Tumpach (Vancouver, CA); Md. Zulfiquar Ali Bhotto (Surrey, CA); Ivan Bajic (West Vancouver, CA); Stephen William Makonin (Burnaby, CA)
Assignee: Rainforest Automation, Inc.
H02J3/32G05B19/042H02J3/381H02J7/0048G05B2219/2639H02J2300/22H02J2300/28
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Quick Facts
Patent No.
US 12,266,938
App. No.
17/494,676
Granted
Apr 1, 2025
Kind
B2
Abstract

Systems and methods for dynamic management of energy usage in local grids are provided. An example method is performed by a load distribution controller coupled to a power source and an energy storage device configured to accumulate power. The method includes acquiring reference levels of using energy of the power source at time slots within a time period and cost values corresponding to the reference levels, dynamically determining, based on the reference levels and the cost values, a schedule indicating charge levels of the energy storage device at the time slots within the time period, and configuring the energy storage device to charge or discharge the power the power according to the schedule. The reference levels are obtained using the Viterbi algorithm based on costs of the energy of power source at past times slots of a past time period and rates of charging and discharging the energy storage device.

Claims (51)

1. A system for dynamic management of energy usage, the system comprising:

at least one power source;

at least one energy storage device configured to accumulate power; and

a load distribution controller coupled to the at least one power source and the at least one energy storage device, the load distribution controller being configured to:

acquire reference levels of using energy of the at least one power source at time slots within a time period and cost values corresponding to the reference levels;

dynamically determine, based on the reference levels and the cost values, a schedule indicating charge levels of the at least one energy storage device at the time slots within the time period, the determining the schedule including:

estimating, based on the reference levels and the cost values of energy from the at least one power source, a reference cost; and

performing feedback loop iterations to match a value of an accumulated cost to the reference cost while modifying the charge levels, wherein the accumulated cost is determined based on the cost values and values of energy demand of using the energy from the at least one power source within the time period, the values of energy demand being one of the following:

a sum of a load demand and an amount of energy required to charge the at least one energy storage device from a first level to a second level of the charge levels; and

a difference between the load demand and an amount of energy obtained by discharging the at least one energy storage device from a third level to a fourth level of the charge levels; and

configure the at least one energy storage device to charge or discharge the power according to the schedule.

2. The system of claim 1 , wherein the load distribution controller includes a proportional-integral-derivative controller configured to perform the feedback loop iterations.

3. The system of claim 1 , further comprising a control device configured to provide the reference levels and the cost values to the load distribution controller.

4. The system of claim 1 , wherein the reference levels are optimized levels of energy determined based on costs of the energy of the at least one power source at past time slots of a past time period and rates of charging and discharging the at least one energy storage device.

5. The system of claim 4 , wherein the past time period is a period determined, based on predetermined criteria, to have the most predictive reference levels.

6. The system of claim 4 , wherein the optimized levels of energy are obtained by a dynamic programming algorithm.

7. The system of claim 6 , wherein the dynamic programming algorithm is Viterbi algorithm.

8. The system of claim 1 , wherein the at least one energy storage device includes at least one of a rechargeable battery, an electric vehicle, a thermal storage device, and a mechanical energy storage device.

9. The system of claim 1 , wherein the at least one power source includes at least one of a Solar panel, a wind power generator, and an electrical grid.

10. A method for dynamic management of energy usage, the method being performed by a load distribution controller coupled to at least one power source and at least one energy storage device configured to accumulate power, the method comprising:

acquiring reference levels of using energy of the at least one power source at time slots within a time period and cost values corresponding to the reference levels;

dynamically determining, based on the reference levels and the cost values, a schedule indicating charge levels of the at least one energy storage device at the time slots within the time period, the determining the schedule including:

estimating, based on the reference levels and the cost values of energy from the at least one power source, a reference cost; and

performing feedback loop iterations to match a value of an accumulated cost to the reference cost while modifying the charge levels, wherein the accumulated cost is determined based on the cost values and values of energy demand of using the energy from the at least one power source within the time period, the values of energy demand being one of the following:

a sum of a load demand and an amount of energy required to charge the at least one energy storage device from a first level to a second level of the charge levels; and

a difference between the load demand and an amount of energy obtained by discharging the at least one energy storage device from a third level to a fourth level of the charge levels; and

configuring the at least one energy storage device to charge or discharge the power according to the schedule.

11. The method of claim 10 , wherein the load distribution controller includes a proportional-integral-derivative controller configured to perform the feedback loop iterations.

12. The method of claim 10 , further comprising providing, by a control device, the reference levels and the cost values to the load distribution controller.

13. The method of claim 10 , further comprising adjusting the reference cost using sub-hourly consumption data and data provided by one or more data sources.

14. The method of claim 10 , wherein the reference levels are optimized levels of energy determined based on costs of the energy of the at least one power source at past time slots of a past time period and rates of charging and discharging the at least one energy storage device.

15. The method of claim 14 , wherein the past time period is a period determined, based on predetermined criteria, to have a most predictive reference levels.

16. The method of claim 14 , wherein the optimized levels of energy are obtained by a dynamic programming algorithm.

17. The method of claim 10 , wherein:

the at least one energy storage device includes at least one of a rechargeable battery, an electric vehicle, a thermal storage device, and a mechanical energy storage device; and

the at least one power source includes at least one of a Solar panel, a wind power generator, and an electrical grid.

18. A system for dynamic energy management of energy usage, the system comprising:

at least one power source;

at least one energy storage device configured to accumulate power;

a control device; and

a proportional-integral-derivative (PID) based load distribution controller coupled to the at least one power source, the at least one energy storage device, and the control device, the PID based load distribution controller being configured to:

acquire, from the control device, reference levels of using energy of the at least one power source at time slots within a time period and cost values corresponding to the reference levels, wherein the reference levels are obtained by Viterbi algorithm based on costs of the energy of the at least one power source at past time slots of a past time period and rates of charging and discharging the at least one energy storage device;

dynamically determine, based on the reference levels and the cost values, a schedule indicating charge levels of the at least one energy storage device at the time slots within the time period, wherein the determining the schedule includes:

estimating, based on the reference levels and the cost values of energy from the at least one power source, a reference cost; and

performing feedback loop iterations to match a value of an accumulated cost to the reference cost while modifying the charge levels, wherein the accumulated cost is determined based on the cost values and values of energy demand of using the energy from the at least one power source within the time period, the values of energy demand being one of the following:

a sum of a load demand and an amount of energy required to charge the at least one energy storage device from a first level to a second level of the charge levels; and

a difference between the load demand and an amount of energy obtained by discharging the at least one energy storage device from a third level to a fourth level of the charge levels; and

configure the at least one energy storage device to charge or discharge the power according to the schedule.

19. The system of claim 3 , wherein the control device includes a physical or virtual gateway device installed in a building.

20. The method of claim 12 , wherein the control device includes a physical or virtual gateway device installed in a building.

21. The system of claim 18 , wherein the control device includes a physical or virtual gateway device installed in a building.

Assignments (2)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Oct 5, 2021
From: JONES, RICHARD THOMAS
To: RAINFOREST AUTOMATION, INC.
Reel/Frame 057708/0537 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Oct 5, 2021
From: BHOTTO, MD. ZULFIQUAR ALI; TUMPACH, CHRISTOPHER STANLEY JAMES; BAJIC, IVAN; MAKONIN, STEPHEN WILLIAM
To: RAINFOREST AUTOMATION, INC.
Reel/Frame 057708/0588 →
Continuity (2)
Provisional Application 63090048 · Oct 9, 2020
Related Publication 20220115872A1 · Apr 14, 2022
References Cited (5)
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US 20200387981A1 · Tinio · 2020 [cited by examiner]
US 20240286515A1 · Tumpach et al. · 2024 [cited by applicant]