A novel algorithm for economic load dispatch of power systems

详细信息    查看全文

• 作者：Xiangzhu He^a ; ^b ; ^{xzhe@mail.scuec.edu.cn" class="auth_mail" title="E-mail the corresponding author}Author Vitae ; Yunqing Rao^aAuthor Vitae ; Jida Huang^cAuthor Vitae
• 关键词：Economic load dispatch ; Chaos search ; CTLBO ; Constraint handling
• 刊名：Neurocomputing
• 出版年：2016
• 出版时间：1 January 2016
• 年：2016
• 卷：171
• 期：Complete
• 页码：1454-1461
• 全文大小：694 K

文摘

Economic load dispatch (ELD) is of great significance for energy saving and emission reduction in power systems. However, many practical constraints and nonlinear characteristics such as valve point effects make this problem a nonlinear constrained optimization problem which is difficult to be solved by traditional optimization techniques. In order to solve this problem effectively, this paper introduces a novel method, chaotic teaching–learning-based optimization with Lévy flight (CTLBO). In the proposed CTLBO, the population is divided into two parts: one is evolved through teaching–learning process, while another part is performed by Lévy flight. Then a chaos perturbation is implemented on the randomly chosen part of population in terms of diversification. Moreover, the proposed method is combined with penalty function to address the constraints. Several numerical cases are adopted and solved to illustrate the effectiveness of the proposed algorithm. And the experimental results are analyzed and compared with existing algorithms, which show that the proposed method outperforms other algorithms and has achieved a significant improvement.