Adaptive energy management system

• US 9,489,701 B2
• Filed: 03/13/2013
• Issued: 11/08/2016
• Est. Priority Date: 11/06/2012
• Status: Expired due to Fees

• Current Assignee: Ali Emadi, Pawel Malysz, Shahin Sirouspour
• Original Assignee: Pawel Malysz, Shahin Sirouspour
• Inventors: Sirouspour, Shahin, Emadi, Ali, Malysz, Pawel
• Primary Examiner(s): Fennema, Robert
• Assistant Examiner(s): Stevens, Thomas
• Application Number:
  US13/800,771
• Publication Number:
  US 20140129040A1
• Time in Patent Office: 1,336 Days
• Field of Search: 700/297
• US Class Current: 1/1
• CPC Class Codes: G06Q 50/06 Energy or water supply
• CPC Class Codes: Y02E 40/70 Smart grids as climate change mitigation technology in the energy generation sector
• 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

Systems, methods, and devices related to a microgrid system for providing power to a facility. A self-contained power system provides power to a facility using a combination of power storage elements and renewable energy sources. A connection to an external power grid may also be provided. The system optimizes power flow to the facility using power from the storage elements and the renewable energy sources and, if necessary, the external power grid. The optimization process predicts future power usage by the facility using power usage data from a predetermined time window. The optimization process can also take into account predicted energy generation amounts by the renewable energy sources. To optimize economic effects, the optimization process can also determine whether to buy and when to buy power from the external power grid.

Claims

1. A system for controlling power flow to a facility, the system comprising:

a controller for controlling said power flow to said facility and for controlling elements of said system;

a power bus for coupling elements of said system to said controller and to one another;

at least one energy storage unit element for storing energy, said at least one energy storage unit element being coupled to said power bus;

at least one renewable energy source for generating power, said at least one renewable energy source being coupled to said power bus;

at least one power load located at said facility, said at least one power load being controlled by said controller;

wherein

said controller controls said power flow to said facility based on at least one of;

geographical data;

occupancy data;

historical data for power consumption of said facility;

operating conditions of said system;

predicted power demands of said system; and

user entered preferences;

said controller predicts an electricity demand of said facility for a succeeding fixed and predetermined future time period based on historical data for power consumption of said facility;

said controller predicts a renewable energy production capacity of said at least one renewable energy source;

said controller determines a net demand for power by said facility based on a predicted electricity demand and on a predicted renewable energy production capacity;

said controller determines whether to draw power from an external power grid based on said net demand for power;

said controller, when necessary, configures said power flow to said facility to an islanded mode wherein, when in islanded mode, said facility is disconnected from said external power grid and said facility only uses power from said at least one renewable energy source and from said at least one energy storage unit element;

said controller optimizes power decisions for said facility using a Mixed Integer Linear Programming formulation using optimization costs which include buying/selling electricity, peak demand, battery usage, battery power signal smoothing, grid connection signal smoothing, and grid connection signal flattening.

2. A system according to claim 1 wherein said system couples to a power grid through said power bus, access to said power grid by said system being controlled by said controller.

3. A system according to claim 2 wherein said controller controls said power flow to said facility based on an optimization process, said optimization process being for optimizing said power flow relative to at least one of:

a cost of power received from said power grid;

an amount of power consumed;

an amount of power generated by said at least one power source element;

an amount of power stored by at least one energy storage unit element;

an amount of power retrieved from said at least one energy storage unit element; and

a user defined provided constraint.

4. A system according to claim 1 wherein said at least one energy storage unit element is at least one of:

a battery;

a capacitor;

an ultra capacitor;

a flywheel;

an electric vehicle equipped with an on-board battery.

5. A system according to claim 1 wherein said at least one renewable energy source is at least one of:

solar power panels;

wind-power turbines.

6. A system according to claim 1 wherein said system further comprises a communications bus, said communications bus being for transmitting communications between said elements and said controller.

7. A system according to claim 3 wherein said optimization process calculates said power flow using at least one of:

weather data;

geographical data;

occupancy data;

historical data for power consumption of said facility;

operating conditions of said system; and

predicted power demands of said system.

8. A system according to claim 1 wherein said at least one renewable energy source is a device which uses at least one of:

hydro-electricity;

biomass technology;

geothermal energy.

9. A method for optimizing operations at a system which controls power flow to a facility, the method comprising:

a) gathering power usage data by said system over a predetermined period of time immediately preceding a set point in time;

b) predicting power usage by said system for a predetermined future period of time based on said power usage data, said predetermined future period of time being immediately succeeding said set point in time;

c) predicting an amount of power generated by renewable energy sources in said system for said predetermined future period of time;

d) determining a net demand for power for said system based on said power usage predicted in step b) and said amount of power predicted in step c);

e) determining whether to draw power from energy storage unit elements in said system for said future period of time based on said net demand for power for said system;

f) determining whether to draw power from an external power grid for said future period of time based on said net demand for power for said system, said external power grid being coupled to said system;

wherein, when necessary, said facility is disconnected from said external power grid and said facility only uses power generated from said renewable energy sources and power stored in said energy storage unit elements;

wherein power decisions for said facility are optimized using a Mixed Integer Linear Programming formulation using optimization costs which include buying/selling electricity, peak demand, battery usage, battery power signal smoothing, grid connection signal smoothing, and grid connection signal flattening.

10. A method according to claim 9 wherein said step of determining whether to draw power from said external power grid is further based on a buying cost of power from said external power grid.

11. A method according to claim 9 further including a step of determining whether to sell power from said system to said external power grid based on a selling cost of power for said external power grid.

12. A method according to claim 9 wherein said renewable energy sources comprises solar cells and said step of predicting an amount of power generated by said renewable energy sources is based on recent weather data.