Modeling and Solution of Economic Dispatch Problem for GTCC Units
- 1 College of Information Engineering, Zhengzhou University, Zhengzhou, China
- 2 College of Electric Power, South China University of Technology, Guangzhou, China
Abstract
Economic dispatch problem lies at the kernel among different issues in GTCC units’ operation, which is about minimizing the fuel consumption for a period of operation so as to accomplish optimal load dispatch among units. This paper has analyzed the load dispatch model of gas turbine combined-cycle (GTCC) units and utilizes a quantum genetic algorithm to optimize the solution of the model. The performance of gas turbine combined-cycle units varies with many factors and this directly leads to variation of model parameters . To solve the dispatch problem, variable constraints are adopted to correct the parameters influenced by ambient conditions. In the simulation, comparison of dispatch models for GTCC units considering and not considering the influence of ambient conditions indicates that it is necessary to adopt variable constraints for the dispatch model of GTCC units. To optimize the solution of the model, a Quantum Genetic Algorithm is used considering its advantages in searching performance. QGA combines the quantum theory with evolutionary theory of genetic algorithm. It is a new kind of intelligence algorithm which has been successfully employed in optimization problems. Utilizing quantum code, quantum gate and so on, QGA shows flexibility, high convergent rate, and global optimal capacity and so on. Simulations were performed by building up models and optimizing the solutions of the models by QGA. QGA shows better effect than equal micro incremental method used in the previous literature. The operational economy is proved by the results obtained by QGA. It can be concluded that QGA is quite effective in optimizing economic dispatch problem of GTCC units.
- T. S. Kim and S. H. Hwang, “Part Load Performance Analysis of Recuperated Gas Turbines Considering Engine Configuration and Operation Strategy,” Energy, Vol. 31, No. 2-3, 2006, pp. 260-277. doi:10.1016/j.energy.2005.01.014
- S. H. Yousef and Najjar, “Comparison of Performance for Cogeneration Systems Using Single- or Twin-shaft Gas Turbine En-gines,” Applied Thermal Engineering, Vol. 17, No. 2, 1997, pp. 113-124. doi:10.1016/S1359-4311(96)00028-2
- B. K. Panigrahi, S. R. Yadav, S. Agrawal and M. K. Tiwari, “A Clonal Algorithm to Solve Economic Load Dispatch,” Electric Power Systems Research, Vol. 77, No. 10, 2007, pp. 1381-1389. doi:10.1016/j.epsr.2006.10.007
- W.-M. Lin, F.-S. Cheng, M.-T. Tsay, “An Improved Tabu Search for Economic Dispatch with Multiple Minima,” IEEE Transactions on Power System, Vol. 17, No. 1, 2002, pp. 108-112. doi:10.1109/59.982200
- C. Yang, Z. L. Yang and R. X. Cai, “Analytical Method For Evaluation of Gas Turbine Inlet Air Cooling in Combined Cycle Power Plant,” Applied Energy, Vol. 86, No. 6, 2009, pp. 848-856. doi:10.1016/j.apenergy.2008.08.019
- C. C. Chuang and D. C. Sue, “Performance Effects of Combined Cycle Power Plant with Variable Condenser Pressure and Loading,” Energy, Vol. 30, 2005, pp.1793-1801. doi:10.1016/j.energy.2004.10.003
- D. Sanchez, R. Chacartegui, J. M. Munoz, A. Munoz and T. Sanchez, “Performance Analysis of a Heavy Duty Combined Cycle Power Plant Burning Various Syngas Fuels,” International Journal of Hydrogen Energy, Vol. 35, 2010, pp. 337-345. doi:10.1016/j.ijhydene.2009.10.080
- C. L. Chen and S. C. Wang, “Branch and Bound Scheduling for Thermal Generating Units,” IEEE Transactions on Energy Conversion, Vol. 8, No. 2, 1993, pp.184-189.
- B. H. Chowdhury and S. Rabman, “A Review of Recent 4dvances in Economic Dispatch,” IEEE Transactions on Power Systems, Vol. PWRS-5, No. 4, 1990, pp. 1248-1257. doi:10.1109/59.99376
- M. Huneault and F. D. Galiana, “Survey of the Optimal Power Flow Literature,” IEEE Transactions on Power Systems, Vol. PWRS-6, No. 2, 1991, pp. 762-770. doi:10.1109/59.76723
- K. Y. Le, A. Sode-Yome and J. Ho, “Park Adaptive Hopfield Neural Networks for Economic Load Dispatch,” IEEE Transactions on Power Systems, Vol. 13, No. 2, 1998.
- R. Naresh, J. Dubey, J. Sharma, “Two Phase Neural Network Based Modeling Framework of Constrained Economic Load Dispatch,” IEE Proceedings-Generation Transmission and Distribution, Vol. 151, No. 3, 2004, pp. 373-378.