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New multi-objectives particle swarm optimization techniques for boiler-turbine power plant / Mohamed Sayed Mohamed Ibrahim ; Supervised Hanan Kamal , Sawsan Morkos Gharghory

By: Contributor(s): Material type: TextTextLanguage: English Publication details: Cairo : Mohamed Sayed Mohamed Ibrahim , 2015Description: 98 P. : facsimiles ; 30cmOther title:
  • تقنيات سرب الجسيمات الأمثل الجديدة متعددة الأهداف لمراجل و توربينات محطة توليد الكهرباء [Added title page title]
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Dissertation note: Thesis (M.Sc.) - Cairo University - Faculty of Engineering - Department of Electronics And Communications Engineering Summary: In this thesis, a new hybrid jump PSO based Gaussian and Cauchy mutation called HJPSO is proposed for optimum tuning of PI controllers parameters of the boiler-turbine unit.Another method is proposed providing a new Pareto solutions based on Euclidean distance for multi-objective particle Swarm optimization named EMOPSO. To achieve the optimal power plant set points that can minimize the fuel consumption and energy losses in the plant, EMOPSO technique is applied to the power plant reference governor.The simulation results of the two new proposed techniques prove their ability to achieve the required targets
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Item type Current library Home library Call number Copy number Status Date due Barcode
Thesis Thesis قاعة الرسائل الجامعية - الدور الاول المكتبة المركزبة الجديدة - جامعة القاهرة Cai01.13.08.M.Sc.2015.Mo.N (Browse shelf(Opens below)) Not for loan 01010110067698000
CD - Rom CD - Rom مخـــزن الرســائل الجـــامعية - البدروم المكتبة المركزبة الجديدة - جامعة القاهرة Cai01.13.08.M.Sc.2015.Mo.N (Browse shelf(Opens below)) 67698.CD Not for loan 01020110067698000

Thesis (M.Sc.) - Cairo University - Faculty of Engineering - Department of Electronics And Communications Engineering

In this thesis, a new hybrid jump PSO based Gaussian and Cauchy mutation called HJPSO is proposed for optimum tuning of PI controllers parameters of the boiler-turbine unit.Another method is proposed providing a new Pareto solutions based on Euclidean distance for multi-objective particle Swarm optimization named EMOPSO. To achieve the optimal power plant set points that can minimize the fuel consumption and energy losses in the plant, EMOPSO technique is applied to the power plant reference governor.The simulation results of the two new proposed techniques prove their ability to achieve the required targets

Issued also as CD

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