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