SYSTEMS AND METHODS FOR MICROGRIDS AVAILABILITY EVALUATION USING A MARKOV CHAIN ENERGY STORAGE MODEL

• US 20130080138A1
• Filed: 07/07/2012
• Published: 03/28/2013
• Est. Priority Date: 09/22/2011
• Status: Active Grant

• Current Assignee: NEC Corporation
• Original Assignee: NEC Laboratories America Inc (NEC Corporation)
• Inventors: Sharma, Ratnesh, Bozchalui, Mohammad Chehreghani
• Granted Patent: US 9,026,411 B2
• Time in Patent Office: Days
• US Class Current: 703/18
• CPC Class Codes: G06F 2111/10 Numerical modelling
• CPC Class Codes: G06F 2113/04 Power grid distribution networks
• CPC Class Codes: G06F 2119/06 Power analysis or power optimisation
• CPC Class Codes: G06F 30/13 Architectural design, e.g. computer-aided architectural design [CAAD] related to design of buildings, bridges, landscapes, production plants or roads
• CPC Class Codes: G06F 30/18 Network design, e.g. design based on topological or interconnect aspects of utility systems, piping, heating ventilation air conditioning [HVAC] or cabling circuit design at the physical level G06F30/39; network planning tools for wireless communication networks H04W16/18
• CPC Class Codes: G06F 30/20 Design optimisation, verification or simulation optimisation, verification or simulation of circuit designs G06F30/30
• CPC Class Codes: G06F 30/25 using particle-based methods

Abstract

Systems and methods are disclosed for availability evaluation of microgrid systems with an energy storage device by applying a Markov chain model to model charging and discharging processes in the energy storage device; determining an effect of the energy storage device connected to a microgrid with multiple energy sources and loads; and determining effect of system architectures on the availability of microgrids using minimum cut sets (MCS).

Claims

1. A method for availability evaluation of microgrid systems with an energy storage device, comprising:

applying a Markov chain model to model charging and discharging processes in the energy storage device;

determining an effect of the energy storage device connected to a microgrid with multiple energy sources and loads; and

determining effect of system architectures on the availability of microgrids using minimum cut sets (MCS).

2. The method of claim 1, comprising generating an energy storage model for reliability evaluation.

3. The method of claim 2, wherein the model comprises a probabilistic model.

4. The method of claim 1, comprising applying a Markov Chain based model.

5. The method of claim 4, wherein the Markov Chain model comprises two states.

6. The method of claim 1, wherein the Markov Chain model comprises a multi-state model that considers charging and discharging states of a storage device.

7. The method of claim 1, wherein the model comprises a deterministic model.

8. The method of claim 1, comprising performing availability evaluation of system architecture.

9. The method of claim 8, comprising modeling components in parallel or in series or in combination.

10. The method of claim 9, comprising applying a deterministic model.

11. The method of claim 9, comprising performing series or parallel modeling.

12. The method of claim 9, comprising applying a probabilistic model.

13. The method of claim 12, comprising applying analytical methods including Boolean algebra or a cut set.

14. The method of claim 12, comprising applying a statistical method.

15. The method of claim 12, comprising applying a Markov-chain Monte Carlo simulation.

16. The method of claim 12, comprising applying a sequential simulation.

17. The method of claim 12, comprising applying an event tree.

18. The method of claim 8, wherein no modeling is required.

19. The method of claim 1, comprising:

determining a state space of (X−

L) for the energy storage system as

S=[−

MΔ

,−

(M−

1)Δ

, . . . , −

2Δ

,−

Δ

,Δ

,2Δ

, . . . , (M−

1)Δ

,MΔ

]

where X and L are the total amount of generated power and load, Δ

is the amount of exchanged energy and M is the maximum number of steps in the presented Markov chain; and

determining the total capacity of the energy storage system as C=M·

Δ

.

20. The method of claim 1, comprising determining a transition probability matrix as:

21. The method of claim 1, comprising determining a loss of load probability (LOLP) as π

_E=Σ

<sub>iε

(1,M)</sub>p<sub>−

i</sub>×

Σ

<sub>j<

L</sub>π

_k where L is an average value of load, π

_E represents LOLP by multiplying the sum of probabilities of discharging in any amount and the sum of limiting probabilities of states that cannot match the power which a load requires.