ELECTRICITY DISTRIBUTION SYSTEM WITH DYNAMIC COOPERATIVE MICROGRIDS FOR REAL-TIME OPERATION

• US 20170194814A1
• Filed: 04/23/2014
• Published: 07/06/2017
• Est. Priority Date: 04/23/2014
• Status: Active Grant

• Current Assignee: NEC Corporation
• Original Assignee: NEC Corporation
• Inventors: CHAKRABORTY, Shantanu, NAKAMURA, Shin, OKABE, Toshiya, MARUHASHI, Kenichi
• Granted Patent: US 10,284,011 B2
• Time in Patent Office: Days
• CPC Class Codes: G05B 13/021 in which a variable is automatically adjusted to optimise the performance
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
• CPC Class Codes: G06Q 50/06 Energy or water supply
• CPC Class Codes: H02J 13/00002 characterised by monitoring
• CPC Class Codes: H02J 13/00022 using wireless data transmission
• CPC Class Codes: H02J 13/00034 the elements or equipment being or involving an electric power substation
• CPC Class Codes: H02J 2300/20 The dispersed energy generation being of renewable origin
• CPC Class Codes: H02J 3/381 Dispersed generators
• CPC Class Codes: H02J 3/46 Controlling of the sharing of output between the generators, converters, or transformers
• CPC Class Codes: Y02B 90/20 Smart grids as enabling technology in buildings sector smart grids supporting the management or operation of end-user stationary applications in general, or like technologies with no associated climate change mitigation effect Y04S20/00
• 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
• CPC Class Codes: Y04S 40/126 using wireless data transmission

Abstract

System and methods for performing microgrids cooperation by optimal coalition formation in a distribution network are disclosed. A Microgrid Cooperation Module (MCM) is designed for utility EMS. MCM contains a coalition formation unit and an energy exchange decision unit. Furthermore, a communication protocol for energy exchange between two microgrids is designed. The coalition formation unit applies an innovative hierarchical coalition formation algorithm to provide optimal coalition for real time operation. The real time energy status of microgrids will be provided to coalition formation unit which will determine the coalitions (given a distance threshold) among microgrids to minimize the power loss. Energy exchange decision unit then determine actual energy transfer between pairs of microgrids within a coalition. Upon receiving the energy transfer information through a communication channel, the microgrids will start communicating and process energy transfer. The optimality of the formed coalitions is ensured by performing coalitional game theoretical analysis.

Claims

1. An electricity distribution system comprising several microgrids and one utility company where, each microgrid must be electrically connected with the utility company by medium voltage line and each microgrid may be connected with other microgrids by low voltage line;

and the utility company and microgrids are interfaced with each other via communication network (e.g. wireless), further comprising;

a utility energy management system (EMS), aims to reduce power loss within network as much as possible.

2. The electricity distribution system as set forth in claim 1, wherein

the utility EMS comprising

a Microgrid Cooperation Module (MCM) which contains two functional unitsCoalition formation unit (CFU) for dynamically form coalitions of microgrids given their energy status which minimizes the power loss in network;

2) An energy exchange decision unit (EDU) for optimized exchange of energy among microgrids within a particular coalition given a distance threshold;

a distribution network profile database that provides necessary spatial and temporal information of microgrids to both CFU and EDU.

3. The electricity distribution system as set forth in claim 2, wherein

the microgrids comprise distributed energy resources and able to periodically declare energy status, that indicates the difference between total demand and total supply to the MCM via communication line.

4. The electricity distribution system as set forth in claim 2, wherein

the CFU is able to process the received energy statues of microgrids and with the help of distribution network profile database can form optimal coalitions of microgrids;

and an optimal coalition of microgrid can ensure

Maximize intra-coalition energy exchange;

Minimized distribution network power loss by utilizing low voltage lines among microgrids;

Reduce energy burden on utility company.

5. The electricity distribution system as set forth in claim 2, wherein

the EDU is able to decide the precise energy exchange profile within a coalition by enabling a predefined distance threshold which states the maximum allowable distance between two microgrids to initiate the energy exchange.

6. The electricity distribution system as set forth in claim 1, further comprising:

a communication protocol for energy exchange between two microgrids.

7. The electricity distribution system as set forth in claim 4, wherein

the CFU comprises a fast and scalable Hierarchical Priority based HR Coalition scheme to provide optimal coalition, in which the optimality property of the HR Coalition scheme is proved by Coalitional Game Theory.