M.M. SALAMA, M.M. ELGAZAR, S.M. ABDELMAKSOUD, H.A. HENRY, "Short Term Optimal Generation Scheduling of Multi-Chain Hydrothermal System Using Constriction Factor Based Particle Swarm Optimization Technique (CFPSO)", International Journal of Scientific and Research Publications, V 3, Issue 4, April 2013, ISSN 2250 - 3153.
International Journal of Scientific and Research Publications • 2013
معلومات البحث
المؤلفون
M.M. SALAMA, M.M. ELGAZAR, S.M. ABDELMAKSOUD, H.A. HENRY
الكلمات المفتاحية
Not Available
المجلة العلمية
International Journal of Scientific and Research Publications
الناشر
Not Available
المجلد
V 3, , ISSN 2250 - 3153.
العدد
Issue 4,
الصفحات
Not Available
publication.type
International
رابط البحث
Not Available
المواد المرفقة
Not Available
الملخص
In this paper, the particle swarm optimization technique with constriction factor is proposed to solve short term multi chain hydrothermal scheduling problem with non
smooth fuel cost objective functions. The performance of the proposed algorithm is demonstrated on hydrothermal test system comprising of three thermal units and four hydro power plants. A wide range of thermal and hydraulic constraints such as power balance constraint, minimum and maximum limits of hydro and thermal units, water discharge rate limits, reservoir volume limits, initial and end reservoir storage volume constraint and water dynamic balance constraint are taken into consideration. The simulation results of the proposed technique are compared with those obtained from other methods such as, simulated annealing (SA) and evolutionary programming (EP) to reveal the validity and verify the feasibility of the proposed method. The test results
show that the proposed algorithm achieves qualitative solution with less computational time when compared to the other methods.
smooth fuel cost objective functions. The performance of the proposed algorithm is demonstrated on hydrothermal test system comprising of three thermal units and four hydro power plants. A wide range of thermal and hydraulic constraints such as power balance constraint, minimum and maximum limits of hydro and thermal units, water discharge rate limits, reservoir volume limits, initial and end reservoir storage volume constraint and water dynamic balance constraint are taken into consideration. The simulation results of the proposed technique are compared with those obtained from other methods such as, simulated annealing (SA) and evolutionary programming (EP) to reveal the validity and verify the feasibility of the proposed method. The test results
show that the proposed algorithm achieves qualitative solution with less computational time when compared to the other methods.
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