Interdisciplinary decision support model for grid-bound heat supply systems in urban areas

摘要

Background In the past two centuries, energy consumption per capita has significantly increased. At the same time the fundamentals of energy provision have continuously developed towards fossil energy sources. This extended use of finite, unequally distributed and emission-intensive energy sources poses a challenge to both the energy, the climate and therefore the socio-ecological systems. Consequently, solutions are needed to reduce the fossil energy demand while fulfilling our daily energy services. District heating systems powered by renewable energy can contribute to this societal mission. Methods This paper presents the co called Eco.District.Heat-kit, a novel planning model supporting future decision-making processes regarding grid-bound heating. The interdisciplinary approach assesses the feasibility of district heating systems at different locations from a qualitative and quantitative perspective. Given the lack of quick and simple planning tools in this field, the Eco.District.Heat-kit provides a time-efficient pre-evaluation on the basis of widely available input data. Results The decision support model rates district heating networks regarding the thematic areas of (1) integrated spatial and energy planning (2) costs, (3) resources, and (4) environment and climate. In addition, it involves a long-term planning horizon by including spatial development and climate scenarios until 2050. Finally, the Eco.District.Heat-kit identifies parameters both positively and negatively influencing the overall rating. This enables end-users to sort out non-optimal configurations before entering a more detailed planning stage. Conclusions Due to the straightforward methodological approach and the focus on basic parameters of district heating system planning, the Eco.District.Heat-kit supports energy suppliers, urban-planners and decision-makers at the beginning of planning processes. In order to increase both transparency and applicability of the model, its functionality and input parameters are disclosed within this paper, enabling the recreation and adaptation towards user-specific needs and local situations.