Economic Dispatch of Combined-Cycle Units

1. Group: May04-11 Economic Dispatch of Combined-Cycle Units http://seniord.ee.iastate.edu/may0411 Project Information Project Requirements Team Members Faculty Advisor Design Objectives Design Constraints • Dr Gerald B. Sheblé • Brent Miller • Marvin Chong • Zobair Molla • Jason Mardorf • To create an algorithm to efficiently • dispatch a combined-cycle unit • To implement the algorithm in • software • Program must be fast • Techniques must be accurate Client • MidAmerican Energy • Des Moines, Iowa Measurable Milestones Functional Requirements Introduction • Understanding the problem and • existing code • Product prototype implementation • Product testing • Must be able to perform economic • dispatch of combined-cycle • generation units • Must provide useful test data Abstract A combined-cycle electric generation plant combines gas-fired combustion turbines and a steam generator. The combustion turbines create a lot of surplus heat, the steam generator compresses this waste heat and uses it as incoming air supply. This greatly increases the efficiency of the plant but also creates non-linear and non-monotonically increasing heat rate curves. Traditional economic dispatch methods fall short in optimizing these kinds of irregular curves. Economic dispatch determines the optimal generation level for each unit generator in order for the system to meet the demand. This project will develop dispatch methods using convex optimization techniques as well as test genetic algorithm techniques. The dispatch calculations will be done in software and tested against other dispatch methods to verify the optimization. The results will mean both economic savings for the client and increased life span of generation units. Proposed Approach and Considerations Proposed Approach Technologies Considered • Review and understand the • problem and data given • Develop an algorithm to solve the • problem • Determine best technology to use • Write a program that implements • the optimization technique • Test the code against data and • previous codes • C++ • C • MATLAB • Fortran Testing Considerations • Testing against theoretical data • Testing against previous programs • Testing against actual data Combined-Cycle Model Estimated Resources and Schedule Personal Efforts Financial Resources GFCT: Gas-Fired Combustion Turbine Problem Statement • Optimization of cost curve for combined-cycle plants • Implement convex optimization in software Project Schedule Limitations Assumptions • Given system representative data • Data in MW range • US power standards • Max and min number of units • Max solution time • Required accuracy Operating Environment Expected End Product Other Resources • A Windows based PC • Minimum 500MHz processor • Program Code: The code performs • the economic dispatch calculations • Test results: The software will be • tested against dispatch calculations • using Genetic Algorithms • Project Poster Closure Materials Intended uses/users Closing Summary Uses Users Economic dispatch for generation facilities are important to consumers and producers because cost is reduced. It also prolongs life of the generation unit by operating at optimal levels. The dispatch calculations require non-traditional methods to optimize the curves. Various algorithms will be used to calculate the optimization. The solution will come in the form of software for the client’s use. • Optimize energy dispatch • Receive system data and determine • settings of generation unit • Provide proof of concept for client • Knowledge of economic dispatch • Power system analysis knowledge • Elementary differential calculus References Acknowledgements • Refined Genetic Algorithm – Economic Dispatch Example • Sheblé, G. B. and Brittig, Kristin • Reserve Constrained Economic Dispatch With Prohibited Operating Zones • Lee, Fred N. and Breipoh, Arthur M. • MidAmerican graciously provided test data and background information to facilitate the project