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Coupling electricity and heat sector is one of the most necessary actions for the successful energy transition. Efficient electrification for space heating and domestic hot water generation is needed for buildings, which are not connected to any district heating network, as distributed heating demand momentarily is largely met by fossil fuels. Hence, hybrid energy systems will play a pivotal role for the energy transition in buildings. Heat pumps running on PV-electricity is one of the most widely discussed combination for this purpose. In this paper, a heuristic optimization method for the optimal operation of a heat pump driven by the objective for maximum onsite PV electricity utilization is presented. In this context, the thermal flexibility of the building and a thermal energy storage (TES) for generation of domestic hot water (DHW) are activated in order to shift the operation of the heat pump to times of PV-generation. Yearly simulations for a system consisting of heat pump, PV modules, building with floor heating installation and TES for DHW generation are carried out. Variation parameters for the simulation include room temperature amplitude (0.5, 1, 1.5 and 2 K) based on mean room temperature (21 °C), PV-capacity (4, 6, 8 and 10 kW) and type of heat pump (ground source and air source type). The yearly energy balances show that buildings offer significant thermal storage capacity avoiding an additional, large TES for space heating fulfillment and improving the share of onsite PV electricity utilization. With introduction of a battery, which has been analyzed as well for different sizes (1.9, 4.8, 7.7 and 10.6 kWh), the share of onsite PVelectricity utilization can even be improved. However, thermal flexibility supplemented by the varying room temperature amplitude for a bigger battery does not improve the share of onsite PV-electricity utilization. Nevertheless, even with a battery not more than 50% of the electrical load including operation of the heat pump can be covered by PV-electricity for the specific system under investigation. This is noteworthy on the one hand, since it indicates that a hybrid heating system consisting of heat pump and PV cannot solely cover the heat demand of residential buildings. One the other hand, this emphasizes the necessity to include further renewable sources like wind power, in order to draw the complete picture. This, however, is beyond the scope of this paper, which mainly focuses on introduction and verification of the novel control method with regard to a practical building.
Micro grids often consist of energy generators, storages and consumers with controllers which are not prepared for their integration into communication networks for energy systems. In this paper it will be presented, how standards from the field of energy automation can be applied in such controllers. The data for communication interfaces can be structured according to the IEC 61850- or the VHPREADY standard. It is investigated which requirements must be supported to implement such data models within the controllers. For the transmission of the data we propose the OPC UA protocol, which supports extensive security measures and which is today available for nearly all modern types of controllers and computers.
This article presents a two-level optimisation approach for the management of controllable and distributed converters with storage systems across different energy sectors. It aims at the reduction of electrical peak load and at the economical optimisation of the electrical energy exchange with the grid, based on a dynamic external incentive, e.g. through dynamic energy price tariffs. By means of a secure, standardised and lean communication with two different internal price signals, an optimal flexibility provision shall be achieved. The two-level optimisation approach consists of a centralised and several distributed decentralised entities. At the centralised level, the distributed flexibilities are invoked for optimal scheduling on the basis of an internal price algorithm for stimulating the decentralised entities. Based on that internal incentive and on the expected demands for electricity, heating and cooling, the decentralised optimisation algorithms provide optimal generation schedules for the energy converters. The suggested interaction between the central and decentral entities is successfully tested and the principle potential for peak shaving and the adaption to dynamic energy-related market prices could be demonstrated and compared to different energy management strategies such as the standard heat-led operation. Further, variations of the system parameters such as load shifting potential, installed capacity and system diversification are evaluated against cost saving potential for the energy supply and overall system performance.