Energy management system in a power and distribution system

• US 20040260489A1
• Filed: 05/12/2004
• Published: 12/23/2004
• Est. Priority Date: 05/13/2003
• Status: Active Grant

• Current Assignee: Siemens AG
• Original Assignee: Siemens Power Transmission & Distribution Incorporated (Siemens AG)
• Inventors: Chen, Dingguo, Peljto, Haso, Mansingh, Ashmin, York, Mike
• Granted Patent: US 7,085,660 B2
• Time in Patent Office: Days
• US Class Current: 702/60
• CPC Class Codes: G06Q 50/06 Energy or water supply
• CPC Class Codes: H02J 2203/20 Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
• CPC Class Codes: H02J 2310/64 The condition being economic, e.g. tariff based load management
• CPC Class Codes: H02J 3/00 Circuit arrangements for ac mains or ac distribution networks
• CPC Class Codes: H02J 3/003 Load forecast, e.g. methods or systems for forecasting future load demand
• CPC Class Codes: Y02B 70/3225 Demand response systems, e.g. load shedding, peak shaving
• CPC Class Codes: Y04S 20/222 Demand response systems, e.g. load shedding, peak shaving
• CPC Class Codes: Y04S 50/10 Energy trading, including energy flowing from end-user application to grid

Abstract

A method and system is provided for optimizing the performance of a power generation and distribution system that monitors the performance of a power system, detects disturbances and calculates statistical information, uses historical performance data and economic factors to analyze and control the production of power. Load demands are predicted by utilizing very short term load forecasts that are based on historical load data, demand patterns and short term load forecasts. Generating units are each assigned a temporal trajectory of output power over consecutive time intervals. The allocation of available resources is assigned so as to minimize costs associated with meeting changing loads.

Claims

1. A method of energy management of a power system, comprising the steps of:

monitoring the performance of the power system, detecting disturbances and calculating statistical information including frequency error;

using historical performance data of the power system and the statistical information to generate a first corrective signal to regulate the generation of power in the power system;

using economic factors to generate a second corrective signal to optimize economic use of power generating resources;

using the first corrective signal and second corrective signal to analyze and generate a control signal to correct the performance of the power distribution system;

dividing a time period into a plurality of sub-periods for use in predicting load demands;

using a plurality of neural networks, each of the plurality of neural networks comprising a plurality of neurons to predict a short term load demand on the power system, the sub-periods being further divided into predicting intervals and assigning one of the plurality of neural networks to each of the plurality of sub-periods;

receiving historical load data and a short term load forecast (STLF) for a STLF interval which is greater than or equal to the largest prediction interval; and

using the output of each of the plurality of neural networks to predict the short term load demand in each predicting interval.

2. The method of claim 1, further comprising the step of determining the ramping constraints of each of a plurality of committed generating units.

3. The method of claim 2, further comprising the step of receiving very short term load predictions for a set of predetermined and consecutive time intervals.

4. The method of claim 3, further comprising the step of obtaining a temporal trajectory of output power for each of the plurality of generating units over the set of predetermined and consecutive time intervals, such that costs associated with changing power output within the power system is minimized.

5. The method of claim 4, further comprising the step of assigning a respective temporal trajectory of output power to each of the plurality of generating units.

6. The method of claim 5, further comprising the step of allocating the use of power generating resources based on the control signal generated to correct the performance of the power system.

7. The method of claim 6, further comprising the step of categorizing a type of performance error and assigning a priority level to the type of performance error.

8. The method of claim 7, further comprising the step of executing corrective action based on the priority level assigned to the type of performance error.

9. A method of energy management of a power system, comprising the steps of:

monitoring the performance of the power system, detecting disturbances and calculating statistical information including frequency error;

using historical performance data of the power system and the statistical information to generate a first corrective signal to regulate the generation of power in the power system;

using economic factors to generate a second corrective signal to optimize economic use of power generating resources; and

using the first corrective signal and second corrective signal to analyze and generate a control signal to correct the performance of the power system; and

determining the ramping constraints of each of a plurality of committed generating units; and

obtaining a temporal trajectory of output power for each of the plurality of generating units over a set of predetermined and consecutive time intervals, such that costs associated with changing power output within the electrical power system is minimized.

10. The method of claim 9 further comprising the step of receiving very short term load predictions for the set of predetermined and consecutive time intervals;

11. The method of claim 10, further comprising the step of assigning a respective temporal trajectory of output power to each of the plurality of generating units.

12. A computer-readable medium having stored thereon instructions which when executed by a processor, cause the processor to perform the steps of:

detecting disturbances and calculating statistical information including frequency error;

using historical performance data of the power system and the statistical information to generate a first corrective signal to regulate the generation of power in the power system;

using economic factors to generate a second corrective signal to optimize economic use of power generating resources; and

using the first corrective signal and second corrective signal to analyze and generate a control signal to correct the performance of the power system;

determining the ramping constraints of each of a plurality of committed generating units; and

obtaining a temporal trajectory of output power for each of the plurality of generating units over a set of predetermined and consecutive time intervals, such that costs associated with changing power output within the electrical power system is minimized.

13. A system for managing a power system, comprising

a monitoring module for monitoring the performance of the power system, for detecting disturbances and for calculating statistical information including frequency error;

a control module in communication with the monitoring module for processing the statistical information generated by the monitoring module and for generating a first corrective signal to regulate the generation of power in the power system;

a control decision module in communication with the control module for analyzing and generating a control signal to correct the performance of the power system;

an economic dispatch module in communication with the control decision module for using economic factors to generate a second corrective signal to optimize economic use of power generating resources, wherein the control decision module uses both the first corrective signal and the second corrective signal to analyze and determine a corrective course of action, represented by the control signal generated by the control decision module; and

a processor for dividing a time period into a plurality of sub-periods and prediction intervals, the processor receiving and processing historical load data and a short term load forecast (STLF) for a STLF interval which is greater than or equal to the largest prediction interval and wherein the first corrective signal and second corrective signal are used to analyze and generate a control signal to correct the performance of the power system.

14. The system of claim 13, further comprising a plurality of neural networks, each of the plurality of neural networks comprising a plurality of neurons to predict a short term load demand on the power system, the sub-periods being further divided into predicting intervals and assigning one of the plurality of neural networks to each of the plurality of sub-periods.

15. The system of claim 14, wherein the output of each of the plurality of neural networks is used to predict the short term load demand in each predicting interval.

16. The system of claim 15, wherein the processor is operative for determining the ramping constraints of each of a plurality of committed generating units and receiving very short term load predictions for a set of predetermined and consecutive time intervals.

17. The system of claim 16, wherein the processor obtains a temporal trajectory of output power for each of the plurality of generating units over the set of predetermined and consecutive time intervals, such that costs associated with changing power output within the electrical power system is minimized.

18. The system of claim 17, wherein the processor assigns a respective temporal trajectory of output power to each of the plurality of generating units.

19. The system of method of claim 19, wherein the processor calculates statistical information comprising calculated real-time statistical data and statistical data based on historical data.

20. The system of claim 19, wherein the processor is operative for determining the available power generating resources and the time need to correct the disturbance and using the determined available power generating resources and time needed to correct the disturbance to generate the first corrective signal.

21. The system of claim 19, wherein the processor is operative for ignoring the generation of the first corrective signal in the event that either the available power generating resources or the time available to correct the disturbance within a predetermined time period is insufficient to take corrective action.