Abstract The primary objective of CDEED (combined dynamic economic emission dispatch) problem is to determine the optimal power generation schedule for the online generating units over a time horizon considered and simultaneously minimizing the emission level and satisfying the generators and system constraints. The CDEED problem is bi-objective optimization problem, where generation cost and emission are considered as two competing objective functions. This bi-objective CDEED problem is represented as a single objective optimization problem by assigning different weights for each objective functions. The weights are varied in steps and for each variation one compromise solution are generated and finally fuzzy based selection method is used to select the best compromise solution from the set of compromise solutions obtained. In order to reflect the test systems considered as real power system model, the security constraints are also taken into account. Three new versions of DHS (differential harmony search) algorithms have been proposed to solve the CDEED problems. The feasibility of the proposed algorithms is demonstrated on IEEE-26 and IEEE-39 bus systems. The result obtained by the proposed CSADHS (chaotic self-adaptive differential harmony search) algorithm is found to be better than EP (evolutionary programming), DHS, and the other proposed algorithms in terms of solution quality, convergence speed and computation time.