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Design of an Optimal Poly-Generation Plant Using Evolutionary Optimization Techniques

Shahhosseini, Hamidreza | 2014

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 45400 (06)
  4. University: Sharif University of Technology
  5. Department: Chemical Engineering and Petroleum
  6. Advisor(s): Pishvaie, Mahmoudreza
  7. Abstract:
  8. In the present study by subject optimal structure design of a polygeneration process, has been trying to obtain an optimal structure of a simultaneous production of methanol and power with the approach of green design based on economic and environmental criteria, discussed and examined. In fact, a new approach to green design solution removes environmental pollutants, not just the final refinement rather tried from the beginning to the process, which is designed to produce less pollution. This period coincides took the idea that design engineers concluded that in order to achieve an optimum design, putting together the correct process equipment is effective as design of the individual instruments. Therefore, new approaches to find the optimal structure of simultaneous production process, which seek to maximize the objective function value economic targets, the emissions are also minimized. Hence in this case we are faced with a problem of multi optimal. So after drawing the Pareto space of economic and environmental objective functions as the introduction of multi optimal process, the optimal structure of simultaneous production of methanol and electricity by numerical methods (division and integration of target functions) delivered to a common problem of optimal with an one objective function and then uses genetic algorithms as optimization algorithm finding the optimal structure of methanol and electricity cogeneration process can be defined and explained. The results shows that the optimal process integration based on economic and environmental objective functions, (while in the second scenario the optimal rigs produce 200 MW of electricity and 400 tons per day of methanol as the market demand), has better economic and environmental performance rather than optimal structure results from first scenario of multiobjective optimization
  9. Keywords:
  10. Genetic Algorithm ; Mixed Integer Programming ; Multiobjective Optimization ; Cogeneration ; Pareto Curve

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