Dimensions
DimensionsMahdi, F.P. and Vasant, P. and Rahman, M.M. and Abdullah-Al-Wadud, M. and Watada, J. and Kallimani, V. (2017) Quantum particle swarm optimization for multiobjective combined economic emission dispatch problem using cubic criterion function. In: UNSPECIFIED.
Full text not available from this repository.Abstract
In this research, quantum particle swarm optimization (QPSO) is utilized to solve multiobjective combined economic emission dispatch (CEED) problem formulated using cubic criterion function considering a uni wise max/max price penalty factor. QPSO is implemented on a 6-unit power generation system and compared with Lagrangian relaxation, particle swarm optimization (PSO) and simulated annealing (SA). The obtained results verified the effectiveness and demonstrate the robustness of QPSO method. This research suggests that QPSO can be used as an effective and robust tool in other power dispatch problems. © 2017 IEEE.
| Item Type: | Conference or Workshop Item (UNSPECIFIED) |
|---|---|
| Additional Information: | cited By 17; Conference of 2017 IEEE International Conference on Imaging, Vision and Pattern Recognition, icIVPR 2017 ; Conference Date: 13 February 2017; Conference Code:127153 |
| Uncontrolled Keywords: | Electric load dispatching; Multiobjective optimization; Pattern recognition; Simulated annealing, Combined economic emission dispatch; Combined economic emission dispatches (CEED); Cubic function; LaGrangian relaxation; Penalty factor; Power generation systems; Price penalty factor; Quantum particle swarm optimization, Particle swarm optimization (PSO) |
| Depositing User: | Mr Ahmad Suhairi UTP |
| Date Deposited: | 09 Nov 2023 16:20 |
| Last Modified: | 09 Nov 2023 16:20 |
| URI: | https://khub.utp.edu.my/scholars/id/eprint/8766 |
Actions (login required)
- View Item