Economic Dispatch of Combined-Cycle Generators

1. Economic Dispatch of Combined-Cycle Generators May06-07 Client: MidAmerican Energy Company Alan Oneal Faculty Advisors: Dr. John Lamont Students: Matthew Ellis, EE Noraima Fernandez, EE Jeremy Hamilton, EE Robert Walter, EE

2. Presentation Overview • Background Material • Previous Teams’ Contributions • Project Team Goals • Main Menu • Overall Structure • Unit Commitment • Output Data • Time Permitting Work • Conclusion/Questions Usability

3. Acknowledgements The senior design project team would like to acknowledge: • Alan Oneal of MidAmerican Energy as our client contact for the project • Dr. Lamont for advising and overseeing the project

4. Overall Project Idea • To incorporate combined-cycle generator units into the current power system to meet peak load emergency • To solve for economic dispatch of monotonic and non-monotonic units, providing the least cost solution Monotonic(MU)→ ←Non-Monotonic (NMU)

5. General Problem Statement The project involves: • modification of an algorithm incorporated into Microsoft Excel macros offering a low-cost and time efficient solution in meeting power demand • use of monotonic and non-monotonic generation systems to provide more cost effective generation dispatch combinations

6. Initial Project Work 1/5 What’s already been accomplished by prior teams…. • Overview • Data Loading and Verification • User specified Excel fields are read into a corresponding VB data array • Data is checked to assure it’s in the correct format and none is missing • If data is incorrect an error window pops into the screen and a log is produced

7. Initial Project Work 2/5 • Algorithm (How does it work?) • MW vs. IHR and I/O are used to calculate A, B, and C coefficients relating each generator’s power and cost Fuel = Ax2 + Bx + C x = Power (MW) dF/dX = IHR = 2Ax + B

8. Initial Project Work 3/5 • Monotonic vs. Non-Monotonic? • A < 0 = Non-Monotonic! • If NMU • Determines 7th order coefficients that relates CT to HRSG output • Uses regression and Solver add-in to solve for each coefficient • Makes a NMU table relating power to cost for every NMU generator • If MU • Makes a MU table relating power to cost for every MU generator

9. Initial Project Work 4/5 • Consolidation • Reads in Unit Commitment Table • For every hour all dispatchable NMU generators are consolidated into a master NMU power vs. cost table • For every hour all dispatchable MU generators are consolidated into a master MU power vs. cost table • Solution • For a desired power output, the program loops through the master MU and NMU tables and finds the least cost solution • Goes into each MU and NMU table and loads each individual power and cost given the master’s power and cost

10. Initial Project Work 5/5 • Client’s Conclusion • The algorithm and program are working correctly and efficiently; however, are extremely confusing to use.

11. General Solution Approach • The project team will modify the existing software to increase the usability in 4 main areas • Main Menu • Overall Structure • Unit Commitment • Output

12. Main Menu 1/6 • Prior Groups’ Main Menu

13. Main Menu 2/6 • Client’s Comments on Existing Menu • Extremely Confusing • Didn’t understand what output options meant • Didn’t understand what format data outside the menu had to be in • Couldn’t find the appropriate places in the workbook to input data

14. Main Menu 3/6 • New Main Menu • Step by Step like a brief instruction manual • Every User Specified Worksheet (data the user can change) will have a step dedicated to it. • Each step will include: • Description of the worksheet • How to change the data • Acceptable data/data format • A hyperlink to the appropriate worksheet • A hyperlink to more detail instructions if desired • Output Options • Each option will have brief description • Scroll Down Lists • Visually Appealing Format • Troubleshooting Links

15. Main Menu 4/6 • Structure

17. Main Menu 5/?

18. Overall Code Structure 1/5 • Client Requests • Have the ability to enter a start and end hour (1-168) • Find solutions for only a range of hours specified

19. Overall Code Structure 2/5 • Dispatching only a range of hours • Code must be completely ran once • Visual Basic Modifications: • A completely different set of modules will be written (many won’t have to change168) • Any data set that doesn’t change will not be re-read in (stored in memory) • Unit-Commitment and Gen Limits will only be read in for user specified hours • Algorithm will only dispatch user specified hours

20. Overall Code Structure 3/5 • Secondary Menu • Will mimic the Main Menu; however common instructions are more vague • Increased Number of User Options • Start/Stop Hours in Scroll Down lists • Unit Commitment, Gen Limits, CT vs. HRSG, etc. data changed? • Set existing unit commitment to default? • Opposite Color Scheme

21. Main Menu 6/?

22. Main Menu 6/?

23. Unit Commitment Page 1/9 • Client’s Comments on Unit Commitment page • Should have statistics on top of page • Doesn’t allow changes in current configuration • Should be able to reset to default commitment pattern • Should consider a number < 0 or a blank to mean the unit is not available • Should check any changes made to ensure that generators up and down times are not violated

24. Unit Commitment Page 2/9 Existing Unit Commitment Page will updated to include the following features: • Calculate the following statistics per hour for a given unit commitment pattern: • Maximum generation capability • Reserve • Generation requirement • Foot room • Minimum generation requirement

25. Unit Commitment Page 3/9 Definitions… • Maximum generation capability = The sum of all committed units’ maximum generation capability • Reserve = The maximum generation capability minus the load requirement • Generation requirement = The total required load • Foot room = The generation requirement minus the minimum generation capability • Minimum generation capability = The sum of all committed units’ minimum generation capability

26. Unit Commitment Page 4/9 • The calculations for the statistics will be made by the following: • IF statements will be used within the Excel worksheet • The IF statement checks the status of each generator for the given hour • If the generator has a blank or zero, the generator is considered off/unavailable • If the generator has a one then it is considered on/available and ready for dispatch • The IF statement then calculates the statistics based on the status of the generators

27. Unit Commitment Page 5/9 The Updated Unit Commitment Page

28. Unit Commitment Page 6/9 • If < 0 or a blank treat as a zero (i.e. not available) • The above change will be made within the visual basic code that loads in the unit commitment data • Master reset button, that loads the default unit commitment pattern from a separate worksheet • The reset button is written in a separate macro which allows a reset of the Unit Commitment table at any given time

29. Unit Commitment Page 7/9

30. Unit Commitment Page 8/9 • A up and down time checker for any given Unit Commitment pattern • The unit commitment checker will be written in a separate visual basic macro • The macro can be ran after each change made to the unit commitment pattern • Any violations of up or down times for the generators will be noted within the unit commitment table in orange

31. Unit Commitment Page 9/9

32. Output Page 1/5

33. Output Page 2/5 • Client’s Comments on Existing Output Sheet • Move statistical data to top of output • Separate output tables • Replace zeros with blanks • Remove units that are not committed • Insert linear hour

34. Output Page 3/5

35. Output Page 4/5

36. Output Page 5/5

37. Time Permitting/Future Work • Graphs consisting of the following data: • Weekly loading, weekly generation per generator and weekly generation for the entire system • Weekly fuel usage for each generator and fuel usage for the entire system • Weekly cost of operation for each generator and cost of operation for the entire system • Possible implementation of a faster solution algorithm

38. Conclusion The project team will modify a software application that will seek to produce the most economical power distribution, with quick solution times, between monotonically and non-monotonically increasing generators.

39. Questions? • Excel