A Modified Shuffled Frog Leaping Algorithm for Nonconvex Economic Dispatch Problem
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A Modified Shuffled Frog Leaping Algorithm for Nonconvex Economic Dispatch Problem
Eiman Sayedi, Malihe M. Farsangi, Mohammad Barati, and Kwang Y. Lee, Fellow, IEEE al. in [3]. To improve the performance of the SFL algorithm, a chaos search is combined with SFL by Li, et al. in [4]. In [5], a new frog leaping rule is introduced and the direction and the length of each frog’s jump are extended by emulating frog’s perception and action uncertainties. Zhen, et al. in [6], introduced a new leaping rule as well as giving a new way for dividing the population. To overcome the difficulties with the SFL, in this paper, a modified SFL (MSFL) is presented by increasing the local search ability of the algorithm. The issue of exploration and exploitation is taken into account by a frog leaping rule for local search and a mimetic shuffling rule for global information exchange. To show the effectiveness of the proposed algorithm, MSFL is tested on economic dispatch (ED) problem which is one of the most important problems to be solved in the operation and planning of a power system [7]. The primary objective of ED problem is to determine the optimal combination of power outputs of all generating units so that the required load demand at minimum operating cost is met while satisfying system equality and inequality constraints. In the traditional ED problem, the cost function for each generator has been approximately represented by a single quadratic function and is solved using mathematical programming based on the optimization techniques such as lambda-iteration method, gradient method, and dynamic programming method, etc. However many mathematical assumptions such as convex, quadratic, differentiable and linear objectives and constraints are required to simplify the problem. The practical ED problem with ramp rate limits, prohibited operating zones, valvepoint effects and multi-fuel options is represented as a non-smooth or nonconvex optimization problem with equality and
A Modified Shuffled Frog Leaping Algorithm for Nonconvex Economic Dispatch Problem
Eiman Sayedi, Malihe M. Farsangi, Mohammad Barati, and Kwang Y. Lee, Fellow, IEEE al. in [3]. To improve the performance of the SFL algorithm, a chaos search is combined with SFL by Li, et al. in [4]. In [5], a new frog leaping rule is introduced and the direction and the length of each frog’s jump are extended by emulating frog’s perception and action uncertainties. Zhen, et al. in [6], introduced a new leaping rule as well as giving a new way for dividing the population. To overcome the difficulties with the SFL, in this paper, a modified SFL (MSFL) is presented by increasing the local search ability of the algorithm. The issue of exploration and exploitation is taken into account by a frog leaping rule for local search and a mimetic shuffling rule for global information exchange. To show the effectiveness of the proposed algorithm, MSFL is tested on economic dispatch (ED) problem which is one of the most important problems to be solved in the operation and planning of a power system [7]. The primary objective of ED problem is to determine the optimal combination of power outputs of all generating units so that the required load demand at minimum operating cost is met while satisfying system equality and inequality constraints. In the traditional ED problem, the cost function for each generator has been approximately represented by a single quadratic function and is solved using mathematical programming based on the optimization techniques such as lambda-iteration method, gradient method, and dynamic programming method, etc. However many mathematical assumptions such as convex, quadratic, differentiable and linear objectives and constraints are required to simplify the problem. The practical ED problem with ramp rate limits, prohibited operating zones, valvepoint effects and multi-fuel options is represented as a non-smooth or nonconvex optimization problem with equality and