Design of an Optimization Algorithm for the Distribution of Thermal Energy Systems and Local Heating Networks within a City District

The linkage of combined heating and power (CHP) systems with local heating networks has the potential to increase energy efficiency on city district scale. First, CHP systems have a high overall efficiency. Second, the usage of CHP systems as heat sources for local heating networks can lead to advantageous economics of scale effects. With an increasing number of buildings the number of possible energy system combinations enlarges tremendously. A manual design approach might lead to a suboptimal solution. This paper describes an approach for the optimized placement of CHP systems, boilers, thermal storages and local heating networks on city district level. A mixed integer linear programming (MILP) problem has been formulated within the General Algebraic Modeling System (GAMS). The objective function is the cost minimization of the overall system under ecological and technical constraints. To reduce the optimization runtime, a k-Medoids demand day clustering and a minimum spanning tree strategy have been implemented. A small city district has been designed as test case. On one hand the algorithm leads to planning solutions with reduced overall costs as well as decreased greenhouse gas emissions. On the other hand a number of 9 buildings leads to 2.5 hours runtime. Therefore, further work on strategies for run time reduction is required.