If you only want the maximum of a single column or a single row, then for large $d$ this is the maximum of $d$ i.i.d. Gaussians with zero mean and variance $1/d$. 

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The maximum of _all_ matrix elements is more subtle:

This problem has been considered in the large-$d$ limit by T. Jiang, <A HREF="https://link.springer.com/article/10.1007/s00440-004-0376-5">Maxima of entries of Haar distributed matrices</A> (alternative
<A HREF="http://users.stat.umn.edu/~jiang040/papers/haar1.pdf">link</A>).

If $W_d$ is the maximum matrix element in absolute value of a Haar-distributed $d\times d$ unitary matrix, then $W_d^2\rightarrow (2/d)\log d$ in probability for $d\rightarrow\infty$.

Numerical simulations that show the convergence of the probability distribution of $W_n$ in the case of random orthogonal matrices are given in <A HREF="https://www.semanticscholar.org/paper/Uncertainty-principles-and-ideal-atomic-Donoho-Huo/64a4094ccbbb7f00491b25ac9089b7b6a58be721">Uncertainty principles and ideal atomic decomposition</A>.