Master's Thesis Christian Schwager

 

Cost-Optimal Design of Decentralized Energy Conversion Units in a Combined Electrical and Thermal Grid

Distributed energy systems provide the potential for reducing CO2 emissions due to improved overall
efficiency and high flexibility with regard to the integration of renewable energy sources. Despite
of financial support from the government, high investments must be compensated by low demand
related costs and additional revenues to maintain competitiveness in the energy market. This can
be achieved by optimizing the mix of different energy conversion technologies, the energy distribution
as well as the integration of energy storages.
This work presents a mixed integer linear programming (MILP) approach for a cost optimal design
of energy systems in domestic buildings. The technologies considered are condensing boilers,
combined heat and power (CHP) units, heat pumps (HP), electrical heating elements and photovoltaic
(PV) systems. In addition, thermal and electrical storages as well as micro-grids (MG) and
local heating networks (LHN) are considered. The optimization process comprises the selection of
technologies for each building as well as the design of unit capacities and the local heating network.
The objective function, which is formulated as total annual costs, is minimized while satisfying the
electrical and thermal demands of the whole neighborhood.
Furthermore, common time series aggregation methods are compared to each other. For this matter,
reference optimizations based on non-aggregated input data are carried out to quantify the
accuracy and relative time savings of the investigated aggregation method. A novel approach, that
enables shorter solving time while conserving the accuracy of the optimal solution, is developed
and applied to theMILP model.
The results reveal that battery storage systems achieve significant CO2 emissions reduction but are
however economically inefficient. Further, the combination of CHPs and HPs in neighborhoods
withMG and LHN achieves CO2 emissions reduction coupled with annual cost savings.