Firefly algorithm for solving non-convex economic dispatch problems with valve loading effect
Yang, Xin-She and Hosseini, Seyyed Soheil Sadat and Gandomi, Amir Hossein (2012) Firefly algorithm for solving non-convex economic dispatch problems with valve loading effect. Applied Soft Computing, 12 (3). pp. 1180-1186. ISSN 1568-4946
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Official URL: http://dx.doi.org/10.1016/j.asoc.2011.09.017
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The growing costs of fuel and operation of power generating units warrant improvement of optimization methodologies for economic dispatch (ED) problems. The practical ED problems have non-convex objective functions with equality and inequality constraints that make it much harder to find the global optimum using any mathematical algorithms. Modern optimization algorithms are often meta-heuristic, and they are very promising in solving nonlinear programming problems. This paper presents a novel approach to determining the feasible optimal solution of the ED problems using the recently developed Firefly Algorithm (FA). Many nonlinear characteristics of power generators, and their operational constraints, such as generation limitations, prohibited operating zones, ramp rate limits, transmission loss, and nonlinear cost functions, were all contemplated for practical operation. To demonstrate the efficiency and applicability of the proposed method, we study four ED test systems having non-convex solution spaces and compared with some of the most recently published ED solution methods. The results of this study show that the proposed FA is able to find more economical loads than those determined by other methods. This algorithm is considered to be a promising alternative algorithm for solving the ED problems in practical power systems.
|Keywords (uncontrolled):||Economic load dispatch; Valve loading effect; Firefly Algorithm; Metaheuristic|
|Research Areas:||A. Middlesex University Schools and Centres > School of Science and Technology > Design Engineering and Mathematics|
|Deposited On:||15 Nov 2012 14:31|
|Last Modified:||25 Feb 2015 17:48|
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