4th generation district heating and cooling networks (shortly THERNETs) are often coined as a crucial technology to enable the transition towards low-carbon smart energy systems. Most importantly, they open perspectives for integration of low-grade residual heat from industry, renewable energy sources (such as geothermal heat and cold and solar thermal collectors), more efficient energy conversion units (such as collective heat pumps), while thermal energy storage (TES) systems increase system flexibility. In order to optimize design and control of such complex systems, a toolbox modesto (Multi-objective district energy systems toolbox for optimization) is under development. However, the representation of seasonal heat and cold storage systems on an annual basis requires large computational power. In an attempt to decrease computational cost, a technique with representative time slices (inspired by and combining aspects from optimization studies of electrical energy systems, unit commitment problems, thermal systems with short term energy storage and smaller scale industrial thermal systems with longer term energy storage) is developed and tested. The aim of this study is to investigate the applicability of such representative time periods to optimize seasonal TES systems in THERNETs. To this end a full year optimization is compared to one with representative time periods for a realistic case study that uses demand profiles from the city of Genk (Belgium) and energy system parameters from Marstal (Denmark). This comparative study shows that modelling with representative periods is sufficient to mimic the behaviour of a full year optimization. However, when curtailment of solar heat injection occurs, not all representations yield the same results. It was found that for the studied case, a selection of 12 representative weeks performs best, while all reduced optimizations result in a substantial reduction (speed-up of on average x4.8 to x7.7) of the calculation time.@en

Due to its inherent large thermal inertia, concrete core activation (CCA) could assist in active demand response schemes. By shifting the injection or extraction of thermal power in time, demand peaks that normally occur more or less simultaneously in clusters of buildings can be spread out in time. Furthermore, thanks to the low temperature differences allowed with respect to the room temperature, CCA is ideally combined with technologies that have increasing renewable potential, such as heat pumps, low temperature district heating and high temperature district cooling. This paper illustrates the flexibility potential of concrete core activation through the exploitation of its thermal energy storage capacity by dynamic simulations. A validated RC thermal model of a CCA is coupled with a detailed building model, including user occupancy and weather disturbances. The flexibility indicator is calculated based on a method presented in the literature, but using an extended version that allows application to more complex systems, including heat losses. Balancing the building between minimal and maximal temperature, the thermal power needed to heat or cool the building can be modulated up- or downward with respect to the reference energy use. The method is applied to various building types with different insulation levels, in order to map the flexibility potential of CCA heating compared to buildings heated with radiators.@en