Self-optimizing hybrid power system

• US 10,230,241 B1
• Filed: 09/30/2016
• Issued: 03/12/2019
• Est. Priority Date: 09/30/2015
• Status: Active Grant

• Current Assignee: the united states of america as represented by the secretary of the navy
• Original Assignee: the united states of america as represented by the secretary of the navy
• Inventors: Rule, Evan T., Shields, Eric B., Lutkenhouse, Crystal P., Trehubenko, John A.
• Primary Examiner(s): Everett, Christopher E.
• Application Number:
  US15/282,517
• Time in Patent Office: 893 Days
• CPC Class Codes: G05B 15/02 electric
• CPC Class Codes: H02J 13/00 Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
• CPC Class Codes: H02J 2300/10 The dispersed energy generation being of fossil origin, e.g. diesel generators
• CPC Class Codes: H02J 2300/24 of photovoltaic origin
• CPC Class Codes: H02J 3/38 Arrangements for parallely feeding a single network by two or more generators, converters or transformers
• CPC Class Codes: H02J 3/381 Dispersed generators
• CPC Class Codes: H02J 7/34 Parallel operation in networks using both storage and other dc sources, e.g. providing buffering H02J7/14 takes precedence
• CPC Class Codes: Y02E 10/56 Power conversion systems, e.g. maximum power point trackers
• CPC Class Codes: Y02E 40/70 Smart grids as climate change mitigation technology in the energy generation sector
• CPC Class Codes: Y02E 60/00 Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
• CPC Class Codes: Y04S 10/123 the energy generation units being or involving renewable energy sources
• CPC Class Codes: Y04S 10/30 State monitoring, e.g. fault, temperature monitoring, insulator monitoring, corona discharge
• CPC Class Codes: Y04S 10/50 Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications

Abstract

An exemplary embodiment of the present invention'"'"'s self-optimizing hybrid power system includes a generator, a solar array, batteries, a GPS, a thermometer, a pyranometer, a power manager, and a computer. The computer: (i) establishes maximum and minimum state-of-charge set points; (ii) receives measurement data from the generator (load), the GPS (location), the thermometer (temperature), and the solar irradiance sensor (solar irradiance); (iii) accesses a historic database that relates to generator load, location, temperature, and solar irradiance; (iv) based on the historic database, predicts a solar profile and a generator load profile; (v) calculates an optimized maximum state-of-charge set point and an optimized minimum state-of-charge set point, based on the predicted solar profile, the predicted generator load profile, the measured location, the measured temperature, and the measured solar irradiance; (vi) transmits control signals to the power manager to vary the maximum and/or minimum state-of-charge set point.

Claims

1. Hybrid power apparatus comprising a generator, a solar energy device, at least one battery, a global positioning system, a thermometer, a solar irradiance sensor, a power manager, and a computer, said computer having computer code characterized by computer program logic for efficiently using said hybrid power, said computer code being executable by said computer so that, in accordance with said computer program logic, said computer performs acts including:

establishing a battery-charging range for said generator, said battery-charging range characterized by a maximum state-of-charge value and a minimum state-of-charge value;

receiving data signals from said generator, said global positioning system, said thermometer, and said solar irradiance sensor, said generator measuring generator loads, said global positioning system measuring location, said thermometer measuring temperature, said solar irradiance sensor measuring solar irradiance;

accessing a historic database relating to said generator loads, said location, said temperature, and said solar irradiance;

predicting a solar profile and a generator load profile, said predicting based on said historic database;

determining an optimized said maximum state-of-charge value and an optimized said minimum state-of-charge value, said determining based on the predicted said solar profile, the predicted said generator load profile, the measured said location, the measured said temperature, and the measured said solar irradiance, wherein at least one of said determining of said optimized maximum state-of-charge value and said determining of said optimized minimum state-of-charge value is performed iteratively;

transmitting control signals to said power manager for varying at least one of said maximum state-of-charge value and said minimum state-of-charge value, said transmitting of said control signals based on the optimized said maximum state-of-charge value and the optimized said minimum state-of-charge value.

2. The hybrid power apparatus of claim 1, wherein said maximum state of charge value is either a fixed maximum state of charge value or a variable maximum state-of-charge value, and wherein said minimum state of charge value is either a fixed minimum state-of-charge value or a variable minimum state-of-charge value.

3. The hybrid power apparatus of claim 1, wherein said state-of-charge value is defined as a percentage of the overall capacity of said at least one battery.

4. The hybrid power apparatus of claim 1, wherein said solar irradiance sensor is a pyranometer.

5. The hybrid power apparatus of claim 1, wherein said generator is an electrical generator.

6. The hybrid power apparatus of claim 1, wherein said generator is a diesel generator.

7. A computer-implemented method for using hybrid power, the computer-implemented method comprising:

establishing a battery-charging range for a generator, said battery-charging range characterized by a maximum state-of-charge value and a minimum state-of-charge value;

receiving data signals from said generator, a global positioning system, a thermometer, and a solar irradiance sensor, said generator measuring generator loads, said global positioning system measuring location, said thermometer measuring temperature, said solar irradiance sensor measuring solar irradiance;

accessing a historic database relating to said generator loads, said location, said temperature, and said solar irradiance;

predicting a solar profile and a generator load profile, said predicting based on said historic database;

determining an optimized said maximum state-of-charge value and an optimized said minimum state-of-charge value, said determining based on the predicted said solar profile, the predicted said generator load profile, the measured said location, the measured said temperature, and the measured said solar irradiance, wherein at least one of said determining of said optimized maximum state-of-charge value and said determining of said optimized minimum state-of-charge value is performed iteratively;

transmitting control signals to said power manager for varying at least one of said maximum state-of-charge value and said minimum state-of-charge value, said transmitting of said control signals based on the optimized said maximum state-of-charge value and the optimized said minimum state-of-charge value.

8. The computer-implemented method of claim 7, wherein said maximum state of charge value is either a fixed maximum state of charge value or a variable maximum state-of-charge value, and wherein said minimum state of charge value is either a fixed minimum state-of-charge value or a variable minimum state-of-charge value.

9. The computer-implemented method of claim 7, wherein said state-of-charge value is defined as a percentage of the overall capacity of said at least one battery.

10. The computer-implemented method of claim 7, wherein said solar irradiance sensor is a pyranometer.

11. The computer-implemented method of claim 7, wherein said generator is an electrical generator.

12. The computer-implemented method of claim 7, wherein said generator is a diesel generator.

13. Hybrid power apparatus comprising a generator, a solar energy device, at least one battery, a global positioning system, a thermometer, a solar irradiance sensor, a power manager, and a computer, said computer having computer code characterized by computer program logic for efficiently using said hybrid power, said computer code being executable by said computer so that, in accordance with said computer program logic, said computer performs acts including:

establishing a battery-charging range for said generator, said battery-charging range characterized by a maximum state-of-charge value and a minimum state-of-charge value;

receiving data signals from said generator, said global positioning system, said thermometer, and said solar irradiance sensor, said generator measuring generator loads, said global positioning system measuring location, said thermometer measuring temperature, said solar irradiance sensor measuring solar irradiance;

accessing a historic database relating to said generator loads, said location, said temperature, and said solar irradiance;

predicting a solar profile and a generator load profile, said predicting based on said historic database;

determining an optimized said maximum state-of-charge value and an optimized said minimum state-of-charge value, said determining based on the predicted said solar profile, the predicted said generator load profile, the measured said location, the measured said temperature, and the measured said solar irradiance;

transmitting control signals to said power manager for varying at least one of said maximum state-of-charge value and said minimum state-of-charge value, said transmitting of said control signals based on the optimized said maximum state-of-charge value and the optimized said minimum state-of-charge value;

wherein said maximum state of charge value is a variable maximum state-of-charge value, and wherein said minimum state of charge value is a variable minimum state-of-charge value.

14. A computer-implemented method for using hybrid power, the computer-implemented method comprising:

establishing a battery-charging range for a generator, said battery-charging range characterized by a maximum state-of-charge value and a minimum state-of-charge value;

receiving data signals from said generator, a global positioning system, a thermometer, and a solar irradiance sensor, said generator measuring generator loads, said global positioning system measuring location, said thermometer measuring temperature, said solar irradiance sensor measuring solar irradiance;

accessing a historic database relating to said generator loads, said location, said temperature, and said solar irradiance;

predicting a solar profile and a generator load profile, said predicting based on said historic database;

determining an optimized said maximum state-of-charge value and an optimized said minimum state-of-charge value, said determining based on the predicted said solar profile, the predicted said generator load profile, the measured said location, the measured said temperature, and the measured said solar irradiance;

transmitting control signals to said power manager for varying at least one of said maximum state-of-charge value and said minimum state-of-charge value, said transmitting of said control signals based on the optimized said maximum state-of-charge value and the optimized said minimum state-of-charge value;

wherein said maximum state of charge value is a variable maximum state-of-charge value, and wherein said minimum state of charge value is a variable minimum state-of-charge value.