The distance between industrial sites and district heating grids as a driver of the economic viability of waste heat integration

Abstract

Industrial waste heat recovery has a great potential to contribute to a sustainable district heating (DH) sector. Consideration of spatial dimension is crucial in implementing waste heat recovery practices. In this paper, we analyze the impact of distance between industrial waste heat sources and DH grids or heat demand points on the economic viability of DH grids and the size of the analysis area on the level of detail for the analysis. For this purpose, we developed a network optimization model that optimizes the topology of a DH network based on heat sources and sinks, analysis area, and various economic and environmental variables such as investment costs and ambient/ground temperature levels. The road network in the analysis area is obtained via Open Street Map. Adding an existing DH grid network into the analysis area is also possible. The problem is solved using mixed-integer linear programming, which is decomposed into two steps to decrease complexity: routing and thermal capacity optimization. After the optimization, heat losses and network costs are calculated. The results are the individual and cumulated pipe lengths, losses, installed pipe capacities, the network costs between source-sink pairs, and visually represented network solution. A separate techno-economic optimization (TEO) model is used to incorporate the time dimension and dispatch of technologies. The TEO model determines the least-cost capacities and operation of technologies considering temporal variations of excess heat availability and heat demands. In the paper, we will apply the model to a case study through varying settings like the size of the analysis area, the number of heat sources and sinks, source and sink potentials, or cost parameters and identify the impact of these parameters on the economic viability of the DH grid and the identification of priority areas for intervention. Also, conclusions regarding prioritization in terms of timing for intervention will be derived. These results could support the industry sector along with decision- and policy- makers, local/regional authorities, or governments to assess the potential for DH investments in a given region/network as an option to improve energy efficiency and contribute to their decarbonization targets.