期刊名称：International Journal of Hybrid Information Technology
印刷版ISSN：1738-9968
出版年度：2016
卷号：9
期号：4
页码：105-116
DOI：10.14257/ijhit.2016.9.4.10
出版社：SERSC
摘要：This paper proposes an Adaptive Cuckoo Search Algorithm (ACSA) for solving economic emission dispatch (EELD) problem with quadratic fuel function. The ACSA is developed by performing two adaptive updated step size parameters on conventional CSA in aim to enhance the convergence speed and quality solution of the conventional CSA. In addition to minimizing electricity generation fuel cost, emission released into the air from thermal plants is also another main objective needs to be minimized. In order to test the performance of the proposed ACSA two systems including a three unit system with one load case and a six unit system with three load cases are employed. The obtained result by the ACSA compared to that from other methods has revealed that the proposed ACSA is a very promising meata-heuristic algorithm for solving economic emission load dispatch problem.
