LAUSR

Abstract Thermo-hydraulic networks are playing an important role in current and future energy systems as they allow to use waste heat and cold improving the overall energy efficiency of the energy system. Additionally, they enable an efficient co-generation of e.g. electricity and heat in one process. Thus, optimal operation of thermo-hydraulic systems is of high interest. Finding an optimal solution for this problem is very challenging, as the energy balances of thermo-hydraulic systems are non-convex being influenced by bilinear terms as well as variable dependent time delays for temperature propagation. Hence, if commitment decisions of several heat or cold generation units are considered, the resulting problem is a non-convex mixed integer nonlinear program (MINLP). Past publications mostly used sequential or iterative approaches to solve this problem not approaching a global optimum. Hence, the quality of their solutions cannot be properly evaluated as no guarantees of convergence to global optimality are given and it is unknown if better solutions exist. In this paper we use multiparametric disaggregation for global optimization of bilinear terms and propose “multiparametric delay modeling” for optimization of variable dependent time delays. Combining the two allows to calculate the gap to global optimality and, hence, results can be used to benchmark other optimization approaches for thermo-hydraulic systems.