Evolutionary programming techniques for different kinds of economic dispatch problems

Economic Dispatch with Multiple Fuel Options Using CCF

“…The comparison of total fuel cost obtained by proposed methodology, HM [9], HNN [10], AHNN [11], HGA [12], Modified PSO (MPSO) [15], TM [16], Improved Fast EP (IFEP) [17], Fast EP (FEP) [17], Classical EP (CEP) [17], PSO [18], and Improved EP (IEP) [19] is presented in Table 2. As seen the comparison, the generation costs obtained by CCF are lowest among the results.…”

“…In order to improve the effectiveness of genetic algorithm multi-stage algorithm and directional crossover methods are proposed and projection method is introduced to satisfy a linear equality constraint from power balance. The heuristic search techniques such as PSO [15] ,Taguchi method (TM) [16], Evolutionary Programming (EP) [17] and its improved version are also been applied to solve the economic dispatch problems with multiple fuel options [18,19].…”

A Simplified Approach for Economic Dispatch with Piecewise Quadratic Cost Functions

“…The total fuel cost for above mentioned load demands obtained by this methodology, Hierarchical Method (HM) [12], Hopfield Neural Network (HNN) [13], Adaptive Hopfield Neural Network (AHNN) [14], Hybrid Genetic Algorithm (HGA) [15], Classical Evolutionary Programming (CEP) [6], Fast Evolutionary Programming (FEP) [6], Improved Fast Evolutionary Programming (IFEP) [6], Particle Swarm Optimization (PSO) [7] and Artificial Immune System (AIS) [16] are compared and the comparison of results are detailed in Table 2. The execution time of the proposed methodology for above mentioned load demands is 0.255 s. 1 212 3 1 266 1 279 1 281 4 3 236 3 239 3 240 5 1 258 1 275 1 278 6 3 236 3 239 3 240 7 1 269 1 286 1 288 8 3 236 3 239 3 240 9 1 331 3 343 3 428 10 1 255 1 272 1 [12] 526.70 574.03 625.18 HNN [13] 526.13 574.26 626.12 AHNN [14] 526.23 574.37 626.24 HGA [15] 526.24 574.38 623.81 IFEP [6] 526.25 ------FEP [6] 526.26 ------CEP [6] 526.25 ------PSO [7] ------623.88 AIS [16] 526 From the comparison of results, it is clear that the proposed approach provides comparable result for economic dispatch problem with piecewise quadratic function. The proposed method has always provided better results than a...…”

“…The stochastic search technique, PSO has been developed by the inspiration of bird flicking characteristics and it has been applied to solve the economic dispatch problems considering various generator operational constraints [5]. Three different evolutionary programming techniques such as Classical EP (CEP), Fast EP (FEP) and Improved Fast EP (IFEP) have been developed with the different mutation techniques and the effectiveness are validated for solving different kinds of economic dispatch problems [6]. The viability of PSO has also been tested for solving different types of economic dispatch problems [7].…”

Economic Dispatch Using Hybrid Particle Swarm Optimization with Prohibited Operating Zones and Ramp Rate Limit Constraints

“…All these methods assume that the cost curve is continuous and monotonically increasing. To overcome the problems of conventional methods for solving ED problems, the researcher's have put into their step by using modern meta-heuristic searching techniques, including Simulated Annealing (SA) [6], Modified Hopfield Network method [7], Genetic Algorithm method (GA) [8], Evolutionary Programming method [9][10][11][12][13], Tabu Search algorithm (TSA) [14], Particle Swarm Optimization method (PSO) [15][16][17][18] have been applied to solve the complex non-linear ED problems. But these methods do not always guarantee a global optimal solution.…”