Loading...

Multi Objective Optimization of a Solid Oxide Fuel Cell/Micro Gas Turbine Integrated System

Behzadi Forough, Atefeh | 2013

655 Viewed
  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 44547 (46)
  4. University: Sharif University of Technology
  5. Department: Energy Engineering
  6. Advisor(s): Roshandel, Ramin
  7. Abstract:
  8. In this project, multi objective optimization (MOO) approach is used to optimize the SOFC/MGT integrated system performance in two strategies. In order to improve the performance and increase of Micro Gas Turbine (MGT) efficiency, it can be combined with Solid Oxide Fuel Cell (SOFC) which it has high operating temperature.The multi-objective optimisation method used allows to generate Pareto curves that represent the trade-off between conflicting thermo-economic objectives of SOFC/MGT integrated system, like, electrical efficiency, output power and electricity cost. The results of the thermo-economic optimization offer a basis for decision making and engineering improvement. SOFC capacity has a significant influence on the electrical efficiency, output power and electricity cost of the integrated power system. In this work firstly, a mathematical model is developed to thermo-economic model a SOFC/MGT integrated system then multi objective optimization is used to optimize the SOFC system in two distinguished strategies. In the first strategy, minimization of the breakeven per-unit energy cost ($/kWh) and maximization of the output power is considered. Similarly, two other objectives are also considered in the second strategy as minimization of the breakeven per-unit energy cost ($/kWh) and maximization of the electrical efficiency. Also multi objective optimization is used to optimize the SOFC/MGT integrated system by considering design and operating parameters as decision variables. The potential of improving the integrated system performance by integrating SOFC with the advanced thermal cycle system and also optimization by considering design parameter is analyzed. Also, two methods are used to multi objective optimization of integrated system: Weighted global criterion method and NSGA II method.Integrated system optimization of the first strategy predicts a maximum power output of 384.21 kW at a breakeven per-unit energy cost of 0.0713 $/kWh and minimum breakeven per-unit energy cost of 0.047 $/kWh at a power of 306.49 kW. In the second strategy, maximum efficiency of 75.8% at a breakeven per-unit energy cost of 0.0711 $/kWh is predicted, while minimum breakeven per-unit energy cost of 0.0469 $/kWh at efficiency of 59.93% is obtained.The results show that the use of integrated system and determination of optimal capacity of SOFC in integrated system lead to different results in two strategies. In the first strategy the average of optimal power increase by 440% while electricity cost decrease by 85.17%. In the second strategy the average of electrical efficiency increase by 21.28% and simultaneously the electricity cost decrease by 82.15%. Also the results delicate that the use of NSGA II method leads to decrease the optimization running time by ratio 1/20 in comparison to weighted global criterion method. On the other hand, the pareto frontier which is obtained by weighted global criterion method has the more monotonous dispersal rather than the NSGA II method
  9. Keywords:
  10. Multiobjective Optimization ; Solid Oxide Fuel Cell (SOFC) ; Genetic Algorithm ; Integrated System ; Microgas Turbine

 Digital Object List

 Bookmark

No TOC