MULTI-AGENT ORIENTED METHOD FOR FORECASTING-BASED CONTROL WITH LOAD PRIORITY OF MICROGRID IN ISLAND MODE

• US 20170262007A1
• Filed: 03/21/2016
• Published: 09/14/2017
• Est. Priority Date: 03/10/2016
• Status: Abandoned Application

• Current Assignee: Macau University of Science and Technology
• Original Assignee: Macau University of Science and Technology
• Inventors: Zhiwu, Li, Abidi, Mohamed Ghaieth, Ben Smida, Moncef, Khalgui, Mohamed, Wu, Naiqi
• Application Number:
  US15/076,643
• Publication Number:
  US 20170262007A1
• Time in Patent Office: Days
• CPC Class Codes: G05B 11/01 electric
• CPC Class Codes: G05B 15/02 electric
• CPC Class Codes: G05B 2219/39407 Power metrics, energy efficiency
• CPC Class Codes: G05F 1/66 Regulating electric power
• CPC Class Codes: H02J 2203/20 Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
• CPC Class Codes: H02J 2300/10 The dispersed energy generation being of fossil origin, e.g. diesel generators
• CPC Class Codes: H02J 3/001 Methods to deal with contingencies, e.g. abnormalities, faults or failures
• CPC Class Codes: H02J 3/003 Load forecast, e.g. methods or systems for forecasting future load demand
• CPC Class Codes: H02J 3/381 Dispersed generators
• CPC Class Codes: Y02E 10/56 Power conversion systems, e.g. maximum power point trackers
• CPC Class Codes: Y02E 10/76 Power conversion electric or electronic aspects
• CPC Class Codes: Y02E 60/00 Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
• CPC Class Codes: Y02P 80/10 Efficient use of energy, e.g. using compressed air or pressurized fluid as energy carrier
• 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
• CPC Class Codes: Y04S 40/20 Information technology specific aspects, e.g. CAD, simulation, modelling, system security

Abstract

The present invention deals with microgrids, which represent a new approach to integrate distributed energy resources economically reliably and efficiently. A microgrid can operate in a connected mode if it makes an energetic exchange with a main grid or in an island mode otherwise. In its island operation mode, a microgrid ensures its energy self-sufficiency. However, the availability of resources in this mode is greatly influenced by meteorological factors and the microgrid must satisfy the high requirements on intelligent power management in order to achieve high availability of energy. The present invention provides a multi-agent control system based on the production forecasting and loads shedding for high availability of the microgrid power supply.

Claims

1. A computer-implemented method for managing connections of sources and loads to a network of a grid to optimize power supply availability, the grid comprising a set of loads, a set of sources, a set of agents for energy management, and a meteorological database having meteorological forecasting data, the method comprising:

collecting, by at least one of the agents, sources production information from the set of the sources;

collecting, by at least one of the agents, loads demand information from the set of the loads;

determining, by at least one of the agents, a power generation level based on the collected sources production information, the loads demand information and the meteorological forecasting data;

connecting or disconnecting, by at least one of the agents, some of the sources to the network based on the power generation level; and

connecting or disconnecting, by at least one of the agents, some of the loads to the network based on the power generation level.

2. The method of claim 1, wherein the set of the loads comprises one or more critical loads and one or more uncritical loads, wherein the critical loads are connected to the network, and the uncritical loads are disconnect-able from the network.

3. The method of claim 1, wherein the set of the sources comprises one or more renewable sources and one or more backup sources.

4. The method of claim 3, wherein the renewable source includes a photovoltaic generator, or a wind turbine.

5. The method of claim 3, wherein generation of the renewable source depends on one or more meteorological factors.

6. The method of claim 3, wherein the stock source includes a battery, or a diesel generator.

7. The method of claim 3, wherein the sources production information includes power produced by the renewable sources and autonomy of the backup sources.

8. The method of claim 3, wherein the loads demand information includes power demand of the critical loads and power demand of the uncritical loads.

9. The method of claim 1, wherein the grid is a microgrid in an island mode.

10. A computer-implemented method for managing connections of sources and loads to a network of a grid to optimize power supply availability, the grid comprising a set of loads, a set of sources, and a set of agents for energy management, the method comprising:

collecting, by a super master production agent, state information of the sources;

collecting, by a super master consumption agent, state information of the loads;

sending, by the super master production agent, a production information token to its related master production agents in order to determine a state of the sources, wherein the production information token visits the master production agents and returns thereafter to the super master production agent;

sending, by each of the master production agents, an internal token to its slaves to collect information on an availability state of their micro-sources;

calculating, by each of the master production agents, the availability state of the sources and filling its own cell in production token information when the master production agent receives the internal token again;

collecting, by the super master consumption agent, information on the loads;

sending, by the super master consumption agent, consumption token information to its related master load agents;

sending, by a priority load agent, an internal load information token to its related slaves in order to determine their energy demands;

calculating, by the priority load agent, a total demand;

filling and passing, by the priority load agent, the internal load information token to a non-priority load agent;

negotiating, by the super master production agent and the super master consumption agent, on a level of production being supplied by available sources to connected loads, while taking into account the information collected by both of the super master production and consumption agents and meteorological forecast information provided by a meteo agent;

sending, by the super master production agent, a control token to the master production agents in order to integrate highest priority available source and disconnect the others;

sending, by master agents of source to be disconnected, control tokens towards their slaves such that they disconnect their microstates;

choosing, by a master agent of the source to be connected, micro-sources to be penetrated while meeting energy requirements, then sending a control token to its slaves; and

coordinating, by the super master consumption agent, with the master load agents in order to connect most priority loads by taking into account the production level.

11. The method of claim 10, wherein the set of the loads comprises one or more critical loads and one or more uncritical loads, wherein the critical loads are connected to the network, and the uncritical loads are disconnect-able from the network.

12. The method of claim 10, wherein the set of the sources comprises one or more renewable sources and one or more backup sources.

13. The method of claim 12, wherein the renewable source includes a photovoltaic generator, or a wind turbine.

14. The method of claim 12, wherein generation of the renewable source depends on one or more meteorological factors.

15. The method of claim 12, wherein the stock source includes a battery, or a diesel generator.

16. The method of claim 10, wherein the grid is a microgrid in an island mode.