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Residential Sector

On a worldwide scale, the residential sector is responsible for 17% of the CO2-emissions. In order to reach the overall goal of net zero CO2-emissions in the second half of this century, a transition of residential energy supply towards a system based on distributed energy resources offers a promising solution. Nevertheless, large scale deployment will have a significant impact on the future electricity grid operation and the traditionally centralized management of energy supply systems.

In order to predict and analyze these changes, our research at the Process and Systems Analysis (VSA) department focuses on modelling the residential sector load in terms of:

  • Self-sufficiency based on distributed energy resources (such as photovoltaics and batteries)
  • Demand side management potential of electricity and heat load
  • Load changes caused by charging of electric vehicles
  • Load reduction due to increasingly efficient conventional electrical consumers and the building refurbishment

A Bottom-Up approach is under development which utilizes a Mixed-Integer Linear Program (MILP) to optimize the energy system design and operation of single buildings or whole districts. The model design allows the manipulation of prices and regulations in order to analyze changes in consumer investment behavior, as well as evaluate potential operational synergies between the considered technologies.
Regarding the high computational load of designing such systems, data aggregation methods are developed to reduce the size of the corresponding optimization problems.

The system modelling, pre- and post-processing is set up in Python while Gurobi® is used as solver for the created MILPs.