We determine the best-fit values and confidence limits for dynamical dark energy parameters together with other cosmological parameters on the basis of different datasets which include WMAP9 or Planck-2013 results on CMB anisotropy, BAO distance ratios from recent galaxy surveys, magnitude-redshift relations for distant SNe Ia from SNLS3 and Union2.1 samples and the HST determination of the Hubble constant. We use a Markov Chain Monte Carlo routine to map out the likelihood in the multi-dimensional parameter space. We show that the most precise determination of cosmological parameters with the narrowest confidence limits is obtained for the Planck{+}HST{+}BAO{+}SNLS3 dataset. The best-fit values and 2$sigma$ confidence limits for cosmological parameters in this case are $Omega_{de}=0.718pm0.022$, $w_0=-1.15^{+0.14}_{-0.16}$, $c_a^2=-1.15^{+0.02}_{-0.46}$, $Omega_bh^2=0.0220pm0.0005$, $Omega_{cdm}h^2=0.121pm0.004$, $h=0.713pm0.027$, $n_s=0.958^{+0.014}_{-0.010}$, $A_s=(2.215^{+0.093}_{-0.101})cdot10^{-9}$, $tau_{rei}=0.093^{+0.022}_{-0.028}$. For this dataset, the $Lambda$CDM model is just outside the 2$sigma$ confidence region, while for the dataset WMAP9{+}HST{+}BAO{+}SNLS3 the $Lambda$CDM model is only 1$sigma$ away from the best fit. The tension in the determination of some cosmological parameters on the basis of two CMB datasets WMAP9 and Planck-2013 is highlighted.