DocumentCode :
3084465
Title :
MOPSO approach to solve profit based unit commitment problem (PBUCP)
Author :
Dhifaoui, Chefai ; Guesmi, Tawfik ; Abdallah, Hsan Hadj
Author_Institution :
Control & Energies Manage. (CEM-Lab.), Nat. Eng. Sch. of Sfax, Sfax, Tunisia
fYear :
2015
fDate :
28-30 April 2015
Firstpage :
175
Lastpage :
182
Abstract :
In this paper a new intelligent technique named multi-objective particle swarm optimization (MOPSO) algorithm used to solve profit based unit commitment (PBUCP). The Profit Based Unit Commitment problem is a nonlinear multi-objective optimization problem which involves the simultaneous optimization to maximize the generation companies (GENCOs) profit. The first function is the revenue while the second is the total cost. This optimization involves many constraints such as system power and reserve, unit generation limit, unit minimum ON OFF duration and ramping constraints. The used technique has been tested on IEEE-39 bus system with ten generating units over 24-h time horizon. The simulation results obtained are compared without another technique. The algorithm and simulation are realized with MATLAB 7.4 software.
Keywords :
particle swarm optimisation; power generation scheduling; power markets; GENCO; IEEE-39 bus system; MATLAB 7.4 software; MOPSO approach; PBUCP; constraints; generation companies; intelligent technique; multiobjective particle swarm optimization; nonlinear multiobjective optimization problem; profit based unit commitment problem; simultaneous optimization; unit generation limit; Energy management; Linear programming; Optimization; Power systems; Production; Schedules; Simulation; Deregulated market; Economic dispatch; GENCO; Market price; Price Based Unit Commitment Problem (PBUCP); multi-objective particle swarm optimization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Systems and Control (ICSC), 2015 4th International Conference on
Conference_Location :
Sousse
Print_ISBN :
978-1-4673-7108-7
Type :
conf
DOI :
10.1109/ICoSC.2015.7153301
Filename :
7153301
Link To Document :
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