Optimal storage sizing for integrating wind and load forecast uncertainties

• US 8,996,187 B2
• Filed: 07/07/2012
• Issued: 03/31/2015
• Est. Priority Date: 07/18/2011
• Status: Active Grant

• Current Assignee: NEC Corporation
• Original Assignee: NEC Laboratories America Inc (NEC Corporation)
• Inventors: Sharma, Ratnesh, Dutta, Sudipta
• Primary Examiner(s): Lo, Kenneth
• Assistant Examiner(s): Rapp, Chad
• Application Number:
  US13/543,817
• Publication Number:
  US 20130024044A1
• Time in Patent Office: 997 Days
• Field of Search: 700/286, 700/291, 700/297
• US Class Current: 700/291
• CPC Class Codes: F05B 2260/8211 of the weather
• CPC Class Codes: H02J 2300/28 The renewable source being wind energy
• CPC Class Codes: H02J 3/003 Load forecast, e.g. methods or systems for forecasting future load demand
• CPC Class Codes: H02J 3/004 Generation forecast, e.g. methods or systems for forecasting future energy generation
• CPC Class Codes: H02J 3/144 Demand-response operation of the power transmission or distribution network
• CPC Class Codes: H02J 3/32 using batteries with converting means
• CPC Class Codes: H02J 3/381 Dispersed generators
• CPC Class Codes: Y02B 70/3225 Demand response systems, e.g. load shedding, peak shaving
• CPC Class Codes: Y02E 10/76 Power conversion electric or electronic aspects
• CPC Class Codes: Y02E 70/30 Systems combining energy storage with energy generation of non-fossil origin
• CPC Class Codes: Y04S 20/222 Demand response systems, e.g. load shedding, peak shaving

Abstract

Systems and methods are disclosed to manage energy system by receiving load forecasts and power generator forecasts with uncertainty specification; performing stochastic optimization on the load and power generation forecasts; determining an optimal storage sizing for energy balancing; and validating the optimal storage sizing; wherein the power generator is connected to an energy storage device with the optimal storage sizing.

Claims

1. A system to manage energy system, comprising:

means for receiving load forecasts and power generator forecasts with uncertainty specification;

means for performing stochastic optimization on the load and power generation forecasts;

means for determining an optimal storage sizing for energy balancing;

means for validating the optimal storage sizing; and

means for minimizing

C_ES·

E_Smax+C_PS·

P_Smax+C_Einit·

E_Sinit

2. The system of claim 1, comprising means for receiving minimum initial stored energy required based on storage characteristics, allowable operational limit.

3. The system of claim 1, comprising means for analyzing various levels of uncertainty of renewable generation forecasts and load forecasts.

4. The system of claim 1, comprising means for receiving reliability indices to measure ‘

goodness’

values and trade-off assessment.

5. The system of claim 1, comprising means for determining loss-of-load probability (LOLP).

6. The system of claim 1, comprising means for determining loss-of-energy probability (LOEP) or spilled-generation-probability (SGP).

7. The system of claim 1, wherein the optimal storage sizing determination further comprises determining optimal energy capacity or optimal power capacity.

8. The system of claim 1, wherein the power generator comprises a wind generator or a solar panel.

9. The system of claim 1, comprising means for applying reliability indices to validate optimal parameters.

10. The system of claim 1, comprising means for performing stochastic linear programming to solve an optimization problem.

11. The system of claim 1, comprising means for applying Monte Carlo based simulations to determine all possible states of the system, thus evaluating the reliability indices.

12. The system of claim 1, comprising means for determining deterministic wind and deterministic load.

13. The system of claim 1, comprising means for determining or estimating stochastic wind and stochastic load.

14. The system of claim 1, comprising means for minimizing the under-generation and loss-of-load probability, and simultaneous minimization of both under-generation and wind spillage.

15. The system of claim 1, comprising code for:

restricting a search space by;

E_Sk+1E_Sk−

P_Sk ∀

k=1,2, . . . N

E_Smin≦

E_Sk≦

E_Smax ∀

k=1,2, . . . N

|P_Sk|≦

P_Smax ∀

k=1,2, . . . N

where P_Smax is a maximum rate of charge or discharge from the storage unit,

E_Smax is a maximum energy limit of the storage,

E_Sk is an energy limit of a storage unit k and E_Sk+1 is an energy limit of a storage unit k+1, and

E_Smin is a minimum energy required in the storage unit at the start of the planning horizon.

16. The system of claim 1, comprising analyzing various levels of uncertainty of renewable generation forecasts and load forecasts.

17. The system of claim 1, comprising receiving reliability indices to measure a ‘

goodness’

of computed values and trade-off assessment.

18. A method to manage energy system, comprising:

receiving load forecasts and power generator forecasts with uncertainty specification;

performing stochastic optimization on the load and power generation forecasts;

determining an optimal storage sizing for energy balancing;

validating the optimal storage sizing;

minimizing

C_ES·

E_Smax+C_PS·

P_Smax+C_Einit·

E_Sinit

19. The method of claim 18, comprising receiving minimum initial stored energy required based on storage characteristics, allowable operational limit.