Algorithm 1 Greedy selection of the measured buses

Input: (1)  Laplacian matrix, $\mathbf{L}$, and noise covariance matrix, $\mathbf{R}$ (2)  Number of buses with sensors, q (3)  Regularization parameter, $\mu$ Output: Subset of q buses, $\mathcal{S}$ 1: Initialize the bus subset ${\mathcal{S}}^{\left(0\right)}=\varnothing$ and the iteration, $i=0$ 2: while$i<q$do 3:    Update the set of available locations, $\mathcal{L}=\mathcal{V}\setminus {\mathcal{S}}^{\left(i\right)}$ 4:    Find the optimal bus to add: $$w^{opt}=arg\underset{w\in \mathcal{L}}{min}\mathrm{Tr}\left(\{\tilde{\mathbf{K}}({\mathcal{S}}^{\left(i\right)}\cup w\},\mu ){\mathbf{R}}_{({\mathcal{S}}^{\left(i\right)}\cup w)}{\tilde{\mathbf{K}}}^T(\{{\mathcal{S}}^{\left(i\right)}\cup w\},\mu )\right),$$ (43) where $\tilde{\mathbf{K}}$ is defined in (27) with ${\mathbf{H}}_{\mathcal{V},\overline{\mathcal{V}}}={\mathbf{L}}_{\mathcal{V},\overline{\mathcal{V}}}$ 5:    Update the subset of buses, ${\mathcal{S}}^{(i+1)}\leftarrow {\mathcal{S}}^{\left(i\right)}\cup w^{opt}$, and the iteration, $i\leftarrow i+1$ 6: end while 7: Update the chosen subset of buses: $\mathcal{S}={\mathcal{S}}^{\left(i\right)}$