Rigorous synthesis of energy systems by relaxation and time-series aggregation to typical periods

The synthesis of energy systems is a complex optimization task depending on multiple large time series. Time-coupling constraints, e.g., due to storage systems, complicate computation even further. To still efficiently solve time-coupled synthesis problems, we propose a rigorous synthesis method. In the proposed method, lower and upper bounds are calculated to obtain a feasible solution of the original synthesis problem with known quality. We compute the lower bound by binary relaxation. For the upper bound, we use time-series aggregation to obtain a feasible design for the system. Employing this feasible design, we solve an operational problem, which can be solved efficiently. To tighten the upper bound, we iteratively increase the time resolution of the aggregation. In a case study for an industrial energy system, we show that only few typical periods are required to obtain a solution of the original synthesis problem with excellent quality. The method has fast convergence outperforming a commercial state-of-the-art solve