基于三次准则函数的多目标组合经济排放调度问题的量子粒子群优化

2017 IEEE International Conference on Imaging, Vision & Pattern Recognition (icIVPR) Pub Date : 1900-01-01 DOI:10.1109/ICIVPR.2017.7890879

Fahad Parvez Mahdi, P. Vasant, M. Rahman, M. Abdullah-Al-Wadud, J. Watada, V. Kallimani

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引用次数: 14

摘要

本文采用量子粒子群算法求解考虑单最大/最大价格惩罚因子的三次准则函数多目标联合经济排放调度问题。在6台发电系统上实现了量子粒子群优化算法，并与拉格朗日弛豫、粒子群优化和模拟退火算法进行了比较。得到的结果验证了QPSO方法的有效性和鲁棒性。这一研究表明，量子粒子群算法可以作为一种有效的鲁棒工具用于解决其他电力调度问题。

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Quantum particle swarm optimization for multiobjective combined economic emission dispatch problem using cubic criterion function

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.

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2017 IEEE International Conference on Imaging, Vision & Pattern Recognition (icIVPR)

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