System, method, and module capable of curtailing energy production within congestive grid operating environments

• US 7,930,070 B2
• Filed: 09/25/2009
• Issued: 04/19/2011
• Est. Priority Date: 09/25/2008
• Status: Expired due to Fees

• Current Assignee: Kingston Consulting, Inc.
• Original Assignee: Kingston Consulting, Inc.
• Inventors: Imes, Kevin R.
• Primary Examiner(s): Jarrett; Ryan A
• Application Number:
  US12/567,394
• Publication Number:
  US 20100076613A1
• Time in Patent Office: 571 Days
• Field of Search: 700/291, 700/297, 700/298, 705/412
• US Class Current: 700/291
• CPC Class Codes: G06Q 50/06 Energy or water supply
• 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

Abstract

A system, method, and module capable of curtailing energy production within congestive grid operating environments, according to are an aspect, including a method of managing power generation of a power generation site operable to be coupled to a transmission line is disclosed. The method can also include detecting a transmission line operating characteristic, and detecting a curtailment action data of the transmission line operating characteristic. Additionally, the method can include determining a forecasted curtailment probability level as a function of the transmission line operating characteristic and the curtailment action data.

Claims

1. A method of managing power generation of a power generation site in communication with at least one transmission line comprising:

transmitting electricity to the transmission line from the power generation site;

employing an information handling system in communication with the transmission line to detect an operating characteristic of the transmission line;

detecting a curtailment action data and a predetermined curtailment probability level of the transmission line;

storing the predetermined curtailment probability level;

analyzing at least the operating characteristic and the curtailment action data to estimate a forecasted curtailment probability level;

comparing the forecasted curtailment probability level to the predetermined curtailment probability level; and

reducing the electricity being transmitted from the power generating site to the transmission line in response to the forecasted curtailment probability level being above the predetermined curtailment probability level to reduce the probability of a future congestion of the transmission line.

2. The method as set forth in claim 1 further comprising:

determining a first price offer of electricity to be sold within a first energy market;

determining a second price offer in response to the forecasted curtailment probability level being above the predetermined curtailment probability level, wherein the second price offer is less than the first price offer and includes an energy output level that is less than a forecasted energy production level; and

outputting the second price offer and the energy output level to the first energy market.

3. The method as set forth in claim 1 wherein said reducing the electricity being transmitted from the power generation site to the transmission line in response to the forecasted curtailment probability level being above the predetermined curtailment probability level comprises re-routing the electricity to a power storage device accessible to the power generation site to store energy within the power storage device.

4. The method as set forth in claim 3 further comprising detecting a high demand transmission line characteristic, and dispatching the stored energy from the power storage device to the transmission line in response to the high demand transmission line characteristic.

5. The method as set forth in claim 1 further comprising communicating the forecasted curtailment probability level to a remote module of the power generation site.

6. The method as set forth in claim 1 further comprising:

detecting historical electricity production data of a plurality of wind generators located at the power generation site;

detecting locally generated historical meteorological data generated at the power generation site;

detecting remotely generated historical meteorological data generated from a different location;

detecting forecasted meteorological data;

analyzing the historical electricity production data, the locally generated historical meteorological data, the remotely generated historical meteorological data, and the forecasted meteorological data to estimate a forecasted energy output level of the power generation site.

7. The method as set forth in claim 6 further comprising analyzing at least the forecasted energy output level and an electricity consumption data and a market pricing information and the forecasted curtailment probability level to estimate a forecasted congestion probability level.

8. The method as set forth in claim 6 further comprising:

altering a power generating factor of at least one of the plurality of wind generators to increase electricity production of the power generation site in response to a forecasted congestion probability level being below a predetermined congestion level; and

detecting the forecasted congestion probability level being above the predetermined congestion level; and

decreasing a power output of at least one of the plurality of power wind generators in response to the detecting of the forecasted congestion probability level being above the predetermined congestion level.

9. The method as set forth in claim 6 further comprising:

detecting non-affiliated historical electricity production data of a plurality of non-affiliated wind generators located at a non-affiliated power generation site;

correlating the non-affiliated historical electricity production data and the forecasted meteorological data;

determining a non-affiliated forecasted energy output level of the non-affiliated power generation site using the correlation of the non-affiliated historical electricity production data and the forecasted meteorological data;

detecting a forecasted congestion probability level using the correlation of the non-affiliated historical electricity production data and the forecasted meteorological data; and

altering operation of power generation site in response to the detected forecasted congestion probability level being above a predetermined congestion level.

10. The method as set forth in claim 1 further comprising:

detecting a congestion transmission line operating characteristic of a portion of a transmission line; and

estimating a forecasted congestion probability level as a function of the congestion transmission line operating characteristic and the curtailment action data; and

altering an output of the power generation site in response to the forecasted congestion probability level being above a predetermined congestion level.

11. The method as set forth in claim 10 further comprising:

estimating the forecasted congestion probability level as as a function of an electricity production data, an electricity transmission data, an electricity consumption data, a meteorological data, a market price data, the curtailment action data, and a non-affiliated wind energy production forecast data;

reducing the electricity being transmitted from the power generation site to the transmission line in response to the forecasted congestion probability level being above the predetermined congestion level; and

increasing the electricity being transmitted to the transmission line in response to the forecasted congestion probability level being below the predetermined congestion level.

12. The method as set forth in claim 1 further comprising:

detecting a grid operating characteristic of a first energy market having a first energy market transmission grid;

detecting a second grid operating characteristic of a second energy market having a second energy market transmission grid;

enabling a coupling of energy produced at the power generation site to a first portion of the first energy market transmission grid or second portion of the second energy market transmission grid in response to a favorable transmission operating environment of either the first energy market transmission grid or the second energy market transmission grid.

13. The method as set forth in claim 1 further comprising:

detecting a dispatch priority of a portion of the transmission line;

determining whether wind energy produced at the power generation site can be output to a first portion of the transmission line; and

enabling an output of the wind energy to the first portion of the transmission line in response to the determination.

14. The method as set forth in claim 1, further comprising:

accessing the transmission line operating characteristic generated by a phasor measurement unit at the power generation site; and

altering an operating condition of a wind power generator at the power generation site using the accessed transmission line operating characteristic.

15. An energy management system configured to manage power generation of a power generation site in communication with at least one communication line, the energy management system comprising:

an information handling system operable to;

detect an operating characteristic of at least one transmission line in communication with a power generation site;

detect a curtailment action data and a predetermined curtailment probability level of the transmission line;

analyze at least the operating characteristic and the curtailment action data to estimate a forecasted curtailment probability level;

compare the forecasted curtailment probability level to the predetermined curtailment probability level; and

a remote module communicatively coupled to the information handling system and operable to;

initiate a transmission of electricity to the transmission line and reduce the electricity being transmitted to the transmission line in response to the forecasted curtailment probability level being above the predetermined curtailment probability level for reducing the probability of a future congestion of the transmission line.

16. The energy management system as set forth in claim 15, the information handling system further operable to:

determine a first price offer of electricity to be sold within a first energy market;

determine a second price offer in response to the forecasted curtailment probability level being above the predetermined curtailment probability level, wherein the second price offer is less than the first price offer and includes an energy output level that is less than a forecasted energy production level; and

output the second price offer and the energy output level to the first energy market.

17. The energy management system as set forth in claim 15 further comprising:

an energy storage device configured to store electricity in response to the information handling system detecting the forecasted curtailment probability level being above the predetermined curtailment probability level; and

wherein the remote module is operable to;

initiate transmission of electricity to the power storage device accessible to the power generation site to store energy within the power storage device in response to the forecasted curtailment probability being above the predetermined curtailment probability level; and

wherein the information handling system is further operable to;

detect a high demand transmission line characteristic; and

dispatch the stored energy from the power storage device to the transmission line.

18. The energy management system as set forth in claim 15, wherein the information handling system is operable to:

detect historical electricity production data of a plurality of wind generators located at the power generation site;

detect locally generated historical meteorological data generated at the power generation site;

detect remotely generated historical meteorological data generated from a different location;

detect forecasted meteorological data;

process the historical electricity production data, the locally generated historical meteorological data, the remotely generated historical meteorological data, and the forecasted meteorological data; and

determine a forecasted energy output level of the power generation site using the processed data.