Vieth, JonathanJonathanViethWestphal, JanJanWestphalSpeerforck, ArneArneSpeerforck2025-08-192025-08-192025-09-01Advances in Applied Energy 19: 100233 (2025)https://hdl.handle.net/11420/57044District heating networks play a critical role in the transition of the heating supply of buildings to renewable sources. The transition from coal-fired or gas-fired generation units to heat pumps requires new planning methods for district heating networks, since the efficiency of a heat pump is affected strongly by the supply temperature of the district heating network. Therefore, a co-planning approach including the operation of the district heating network in the planning process is required. This paper presents a novel co-planning approach consisting of two steps. First, an optimal district heating network topology is generated from real geo-referenced data. To determine the optimal topology, a new algorithm designed specifically for district heating networks is presented. Next, a simulation model is automatically generated from the respective topology. An optimization is used for the co-planning approach to select an optimal generation unit, find the optimal supply temperature, and dimension the pipes of the district heating network. In contrast to conventional district heating network planning procedures, the optimization includes a full-year dynamic simulation of the district heating network. The result of the planning process is a full y parameterized district heating network with a matching supply temperature. Furthermore, the use of simulation models allows the results to be reused for sensitivity analyses. This is illustrated by examining the selection of generation units under different CO<inf>2</inf> price scenarios.en2666-7924Advances in applied energy2025Elsevierhttps://creativecommons.org/licenses/by/4.0/Co-planningDistrict heatingDistrict heating network planningDistrict heating network simulationNetwork routingSocial Sciences::330: EconomicsTechnology::620: EngineeringDistrict heating network topology optimization and optimal co-planning using dynamic simulationsJournal Articlehttps://doi.org/10.15480/882.1578910.1016/j.adapen.2025.10023310.15480/882.15789Journal Article