Many problems in optimization of transportation networks for heat and power can be stated in terms of matrices with non-negative coefficients. Moreover, dynamical models for such systems often have monotone step responses. This has great advantages in design and verification of controllers for large-scale networks. In particular optimal controllers can be computed using linear programming, with a complexity that scales linearly with the number of states and interconnections. Hence two fundamental advantages are achieved compared to classical methods for multivariable control: Distributed implementations and scalable computations. We will present several examples and look forward to discussing the relevance for energy-efficient buildings.