METHODS AND SYSTEMS FOR ENHANCING CONTROL OF POWER PLANT GENERATING UNITS

• US 20160261115A1
• Filed: 03/03/2015
• Published: 09/08/2016
• Est. Priority Date: 03/03/2015
• Status: Active Grant

• Current Assignee: GE Infrastructure Technology, LLC (GE Vernova, Inc.)
• Original Assignee: General Electric Company
• Inventors: Asati, Mahesh Kumar, Tiwari, Awadesh Kumar
• Granted Patent: US 9,960,598 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G05B 19/102 for input of programme steps, i.e. setting up sequence
• CPC Class Codes: G05B 2219/2639 Energy management, use maximum of cheap power, keep peak load low
• CPC Class Codes: H02J 13/00 Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
• CPC Class Codes: H02J 13/00004 characterised by the power network being locally controlled
• CPC Class Codes: H02J 2310/12 The local stationary network supplying a household or a building
• CPC Class Codes: H02J 3/14 by switching loads on to, or off from, network, e.g. progressively balanced loading
• CPC Class Codes: Y02B 70/3225 Demand response systems, e.g. load shedding, peak shaving
• CPC Class Codes: Y02B 90/20 Smart grids as enabling technology in buildings sector smart grids supporting the management or operation of end-user stationary applications in general, or like technologies with no associated climate change mitigation effect Y04S20/00
• CPC Class Codes: Y04S 20/00 Management or operation of end-user stationary applications or the last stages of power distribution; Controlling, monitoring or operating thereof
• CPC Class Codes: Y04S 20/222 Demand response systems, e.g. load shedding, peak shaving

Abstract

A method for optimizing a fleet of generating assets in which groupings include remotely located power blocks that operate so to collectively generate a fleet output level. The method may include: receiving real-time and historical measured values of operating parameters; for each of the generating assets, deriving a relational expression between the measured values of the process inputs and the measured values of the process outputs; defining a selected operating period; selecting competing operating modes for the fleet; based on the relational expressions and a generating configuration of the competing operating modes, calculating a result set for the operation of the fleet proposed during the selected operating period; defining a cost function; and evaluating each of the result sets pursuant to the cost function and, based thereupon, designating one of the competing operating modes as an optimized operating mode. The optimized operating mode may include a power sharing recommendation between the power blocks of the fleet.

Claims

1. A control method for optimizing a fleet of generating assets in which groupings of the generating assets comprise remotely located power blocks that operate so to collectively generate a fleet output level for a market, wherein the fleet comprises multiple possible generating configurations, the method including the steps of:

receiving real-time and historical measured values of operating parameters related to an operation of each generating asset, the measured values of the operating parameters including process inputs and process outputs;

for each of the generating assets, deriving a relational expression between the measured values of the process inputs and the measured values of the process outputs;

defining a selected operating period, the selected operating period representing a prospective operating period for the fleet;

selecting competing operating modes for the fleet for the selected operating period, wherein each competing operating mode defines an unique one of the possible generating configurations of the fleet;

based on the relational expressions and the generating configuration for each of the competing operating modes, calculating a result set for the operation of the fleet proposed during the selected operating period;

defining a cost function; and

evaluating each of the result sets pursuant to the cost function and, based thereupon, designating at least one of the competing operating modes as an optimized operating mode;

wherein the optimized operating mode comprises a power sharing recommendation between the power blocks of the fleet for generating the fleet output level.

2. The method according to claim 1, wherein the relational expressions comprise a fleet model in which asset models correlate the measured values for the process input to the process outputs for each of the generating assets;

further comprising the step of tuning the fleet model via a data reconciliation process that includes;

defining a previous operating period relative to the selected operating period;

based on the measured values of the operating parameters during the previous operating period, determining a measured value for a performance indicator;

deriving a predicted value of the performance indicator using a current version of the fleet model and a predicted value for at least one of the operating parameters, wherein the predicted value of the performance indicator is configured to comparatively correspond to the measured value of the performance indicator;

comparing the measured value of the performance indicator against the predicted value of the performance indicator so to determine a differential therebetween; and

adjusting the current version of the fleet model so to reduce the differential;

wherein the relational expression comprises an algorithm correlating a variability of one or more of the process inputs to a variability of one of the process outputs.

3. The method according to claim 1, wherein the relational expressions collectively comprise a fleet model in which an asset model correlates the measured values for the process input to the process outputs for each of the generating assets;

wherein, for each of the competing operating modes, the step of calculating the result set for the operation of the fleet proposed during the selected operating period includes a simulation run inclusive of the following steps;

defining a proposed parameter set for the competing operating mode;

simulating with the fleet model the operation of the fleet over the selected operating period pursuant to the proposed parameter set; and

determining the result set from an output of the simulation;

wherein the power sharing recommendation comprises a block apportionment schedule dividing the fleet output level between the power blocks.

4. The method according to claim 3, wherein the simulation runs are executed by a common block controller remotely located relative to a plurality of the power blocks;

wherein the selected operating period is configured so to correspond to a future market period as defined by a governing authority of the market; and

wherein the power sharing recommendation comprises an asset apportionment schedule that divides a power block output level between the generating assets included therewithin.

5. The method according to claim 4, further comprising the steps of:

sensing the real-time and the historical measured values of the operating parameters via sensors located at each of the generating assets; and

electronically communicating the real-time and the historical measured values of the operating parameters from each of the generating assets for storage at a common database operably linked and proximate to the block controller.

6. The method according to claim 5, wherein an outside generating asset is defined as a generating asset that operates outside of the fleet and comprises a similar generating configuration as at least one of the generating assets within the fleet;

and

wherein an outside power block is defined as a power block that operates outside of the fleet and comprises a plurality of the outside generating assets;

further comprising the steps of;

receiving outside operating data regarding historical measured values of operating parameters that relate to an operation of a plurality of the outside generating assets and at least one of the outside power blocks; and

storing the outside operating data at the common data base;

wherein the fleet model and the relational expressions included therein are derived, at least in part, based on the outside data.

7. The method according to claim 5, wherein an outside generating asset is defined as one operating outside of the fleet that comprises similar possible generating configurations as one of the generating assets within the fleet;

further comprising the steps of;

receiving outside data regarding historical measured values of the operating parameters that relates to the operation of at least one of;

a plurality of the outside generating assets; and

the outside power block; and

storing the outside data at the common data base; and

normalizing the real-time measured values of the operating parameters of the generating assets of the fleet based on;

the historic measured values of the operating parameters of the generating assets of the fleet; and

the outside data regarding outside generating assets.

8. The method according to claim 7, wherein the step of normalizing the real-time measured values comprises adjusting a current value for a performance indicator based on a measured value of an operational variable so to determine a true value for the performance indicator.

9. The method according to claim 8, wherein the performance indicator comprises one of:

an efficiency; and

a generating capacity;

wherein the operational variable comprises at least one of;

a load level, a fuel characteristic, and an operating parameter relating to ambient conditions; and

wherein the true value for the performance indicator comprises one indicating loss due to performance degradation.

10. The method according to claim 8, further comprising the steps of:

determining an initial value for the performance indicator for each of the generating assets based on the historical measured values for the operating parameters;

periodically determining the true value for the performance indicator for comparison against the initial value for the performance indicator, and, based on a difference therebetween, determining a performance degradation rate for each of the generating assets.

11. The method according to claim 10, wherein the power sharing recommendation is based upon the performance degradation rates determined for the generating assets.

12. The method according to claim 11, wherein the power sharing recommendation is based upon minimizing the performance degradation rates over the selected operating period.

13. The method according to claim 9, further comprising the steps of determining a current state of performance degradation for each of the generating assets based on the true value of the performance indicator.

14. The method according to claim 13, wherein the asset apportionment schedule within at least one of the power blocks is based upon the state of performance degradation for each of the generating assets within the at least one of the power blocks.

15. The method according to claim 13, further comprising the step of summing the current state of performance degradation for the generating assets within each of the power blocks so to determine a block performance degradation rating for each of the power blocks;

wherein the block apportionment schedule is based upon the block performance degradation ratings.

16. The method according to claim 10, further comprising the step of receiving forecasted ambient condition data for the selected operating period;

wherein the proposed parameter sets include the forecasted ambient conditions data.

17. The method according to claim 10, wherein the result set for each of the competing operating modes includes:

a predicted state of performance degradation after the selected operating period based upon;

the degradation rate, and the current state of performance degradation; and

an expended useful part-life;

wherein the cost function is configured to correlate an economic result for each of;

the predicted state of performance degradation; and

the expended useful part-life.

18. The method according to claim 17, wherein the result set of each for each of the competing operating modes includes:

a fuel consumption; and

an output level;

wherein the cost function comprises a correlation of an economic result for each of;

the fuel consumption; and

the output level, including a revenue associated therewith.

19. The method according to claim 16, wherein the power sharing recommendation comprises a weighted optimization based on:

a predicted state of performance degradation;

an expended useful part-life;

a fuel consumption;

an output level, including a revenue associated therewith; and

a fleet emissions.

20. The method according to claim 16, wherein the current state of performance degradation comprises recoverable and non-recoverable degradation;

wherein the power sharing recommendation further comprises;

a maintenance recommendation in which an economic result of continued operation given the current states of degradation is compared against a maintenance schedule including a downtime for at least one of the generating assets whereby a proposed maintenance routine recovers a portion of the recoverable degradation.

21. The method according to claim 20, wherein the remaining useful part-life comprises remaining hours of useful part-life and remaining shutdown startup cycles of useful part-life.

22. The method according to claim 13, wherein the optimized operating mode is based on current performance degradation state so that a predicted degradation state at the end of the selected operating period comprises an optimized one of:

fleet generating capacity and fleet heat rate.

23. The method according to claim 3, further comprising the step of communicating an output based on the optimized operating mode;

wherein the output comprises at least one of;

an electronic override command and a control solution to a plurality of the generating assets; and

a bid to a central dispatch authority; and

wherein the optimized operating mode further comprises at least one of;

a health advisor related to at least one of the power blocks; and

an outage planner for a plurality of the generating assets.

24. The method according to claim 9, wherein the performance indicator comprises at least one of:

thermal and mechanical stress profiles for the generating assets;

performance degradation;

useful part-life expended; and

emission levels.

25. The method according to claim 9, wherein the step of simulating the competing operating modes comprises identifying location dependent variables for inclusion as input data for the fleet model;

wherein the location specific variables comprise at least a plurality of one of;

locality-based fuel price differences between the assets;

locality-based fuel storage differences between the assets;

locality-based revenue earned differences for generated electricity between the assets;

locality-based weather forecast differences between the assets for the future market period; and

locality-based maintenance schedule differences between the assets.