Service-based Approach Toward Management of Grid-Tied Microgrids

• US 20150311713A1
• Filed: 04/07/2015
• Published: 10/29/2015
• Est. Priority Date: 04/28/2014
• Status: Abandoned Application

• Current Assignee: NEC Laboratories America Inc (NEC Corporation)
• Original Assignee: NEC Laboratories America Inc (NEC Corporation)
• Inventors: Asghari, Babak, Sharma, Ratnesh, Hooshmand, Ali
• Application Number:
  US14/680,848
• Publication Number:
  US 20150311713A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: H02J 2203/20 Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
• CPC Class Codes: H02J 3/00 Circuit arrangements for ac mains or ac distribution networks
• CPC Class Codes: Y02E 60/00 Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
• CPC Class Codes: Y04S 40/20 Information technology specific aspects, e.g. CAD, simulation, modelling, system security

Abstract

Systems and methods are disclosed for providing service based interactions between a utility and a microgrid by adjusting power flow profile at a point of common coupling (PCC) between a microgrid and a utility, wherein the power flow profile is adjusted to achieve a predetermined objective function based on a utility request; delivering different services to the utility at different periods of time by altering its internal operation of distributed generators, energy storage units, and demands as a multi-purpose microgrid; and managing the microgrid to deliver services to the utility and reduce its operational cost simultaneously.

Claims

1. A method for providing service based interactions between a utility and a microgrid, comprising:

adjusting power flow profile at a point of common coupling (PCC) between a microgrid and a utility, wherein the power flow profile is adjusted to achieve a predetermined objective function based on a utility request;

delivering different services to the utility at different periods of time by altering its internal operation of distributed generators, energy storage units, and demands as a multi-purpose microgrid; and

managing the microgrid to deliver services to the utility and reduce its operational cost simultaneously.

2. The method of claim 1, comprising providing service-based interaction between a utility and a microgrid.

3. The method of claim 2, comprising a framework in which the interaction between microgrid and utility is based on the service (power profile) which is exchanged at the point of common coupling (PCC).

4. The method of claim 1, wherein the multi-purpose microgrid constantly adjusts its internal operation points (generator, storage and load setpoints) to deliver services at the PCC as requested by the utility.

5. The method of claim 1, comprising providing service-as-a-constraint where a service requested by the utility from the micro grid is a constraint satisfied at the PCC.

6. The method of claim 1, comprising solving an optimization problem to minimize the microgrid operational cost considering all internal constraint plus the constraint imposed by the service request.

7. The method of claim 6, comprising applying the optimization to a schedule for operation of devices in the microgrid during the service period.

8. The method of claim 1, comprising providing service-as-an-objective operation where service requested by the utility is a function minimized or maximized at the PCC.

9. The method of claim 1, comprising performing bi-objective optimization of microgrid cost and service quality.

10. The method of claim 9, comprising solving a bi-objective optimization problem to find an optimal schedule for the micro grid operation when service is an objective.

11. The method of claim 1, comprising solving microgrid operational cost and a service objective function.

12. The method of claim 1, wherein a solution to bi-objective optimization is not unique and includes a set of optimal solutions (Pareto front).

13. The method of claim 12, wherein the Pareto front is used by a management system or an operator to select the optimal schedule for micro grid operation depending on a contract with the utility.

14. The method of claim 1, comprising providing a weighted-sum optimization of the cost and objective function.

15. The method of claim 14, where the weighted-sum method is used to find a Pareto front of the bi-optimization problem.

16. The method of claim 1, comprising applying Epsilon-constraint optimization approach.

17. The method of claim 16, wherein the epsilon-constraint optimization approach is used to find a Pareto front of the bi-optimization problem.

18. The method of claim 1, comprising minimizing costs for a grid-tied microgrid consisting of distributed generations, energy storage units and flexible loads over a time period of T as:

19. The method of claim 1, comprising minimizing

20. The method of claim 1, comprising providing service as a constraint where g must be less than a constant.