You could do a meta-analysis. So analyse them separately and then compute a meta-p value and/or a meta-log2-FC.
I was planning to get the DEGs from individual datasets separately and
then find the common DEGs across the different datasets.
By just using the common genes you could potentially loose a lot of information - in particular if the datasets vary a lot.
Also, you need to account for the different genes interrogated - you mentioned that the datasets all are from the same platform - which is good - but are they also analysed with the same array type? If not, then you need to account for the different number of genes on the arrays.