In this work, a method for taking into account seasonal storage in an energy optimisation problem is developed. A master-slave optimisation procedure is applied, in which the master optimisation is an evolutionary algorithm, while the slave optimisation is a Mixed Integer Linear Programming (MILP) problem. The results of this optimisation can provide insight on the choice of technologies during the study of potential new district heating networks, and especially evaluate if a seasonal storage is worthwhile. The method developed is applied to a case study. The goal is to optimise the design of a micro-district heating system consisting of 3 buildings and a neighbouring source of industrial waste heat. The technologies considered are heat pumps, solar thermal collectors, a hot water storage tank, geothermal borehole seasonal storage, a gas boiler and industrial waste heat. The results show that, with the given assumptions, the use of combined seasonal and daily thermal storage can significantly reduce operating costs (by 65 %), fossil fuel consumption and CO2 emissions, with a payback time of 4.5 years compared to a reference solution with no storage.