Minimizing Electricity Fuel Cost of Thermal Generating Units by Using Improved Firefly Algorithm

Abstract

This paper presents the application of an improved firefly algorithm (IFA) for minimizing total electricity generation fuel cost while all loads are supplied by thermal generating units. The proposed IFA was developed by combining two proposed improvements of the firefly algorithm (FA), i.e. improvement of the distance between two considered solutions and improvement of the new-solution production technique. The effect of each proposed improvement on the conventional firefly algorithm (FA) and the performance of IFA were investigated in two study cases, i.e. single-and multi-fuel option based thermal generating units. In the first case, three different systems with three, six and twenty units were employed, while a ten-unit system with four different loads was tested in the second case. The comparison results between IFA and existing methods, including three other FA variants, revealed that the two proposed improvements of FA are very efficient and make IFA a very promising meta-heuristic algorithm for minimizing fuel cost of thermal generating units.

Modified moth swarm algorithm for optimal economic load dispatch problem

“…The figure shows that MMSA, MSFS [19], GAMS [22], IGSO [23], and ICSA [25] attain the same value and are put at the top group. The rest group has a presence of MFA [18], HM [20], BBO [21], and BSA [24] with the reported results of 62,456.638, 62,456. 634, 62,456.793, 62,456.6933 ($/h), respectively.…”

“…As a result, optimal solutions found by ISSO were better than MPSO and other methods. For 10-unit system, many methods as DE [3], antlion optimization algorithm (ALO) [13], artificial immune system (AIS) method [14], enhanced augmented Lagrange Hopfield network (EALHN) [15], enhanced lagrangian artificial neural network (ELANN) [16], improved quantum-behaved particle swarm optimization (IQPSO) [17], modified firefly algorithm (MFA) [18] and modified stochastic fractal search algorithm (MSFS) [19] have been successfully employed with the impressive results. Among these methods, MSFS is the latest tool that has been formed by proposing three modifications based on the structure of stochastic fractal search (SFS).…”

“…For the last system, several methods are used for OELD problem. They include MFA [18], MSFS [19], Hopfield model (HM) [20], biogeography-based optimization (BBO) algorithm [21], general algebraic modeling system (GAMS) [22], improved group search optimizer (IGSO) [23], backtracking search algorithm (BSA) [24] and improved cuckoo search algorithm (ICSA) [25]. The contribution of the above algorithms is worthy of recognition in dealing with such OELD problem because these algorithms supply different solutions in aim to the most economical and stable power system operation.…”