Demand Side Management Based Power-to-Heat and Power-to-Gas Optimization Strategies for PV and Wind Self-Consumption in a Residential Building Cluster

Marcus Brennenstuhl, Daniel Lust, Dirk Pietruschka and Dietrich Schneider
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Marcus Brennenstuhl: Centre for Sustainable Energy Technology (zafh.net), Stuttgart University of Applied Sciences, Schellingstr. 24, 70174 Stuttgart, Germany
Daniel Lust: Centre for Sustainable Energy Technology (zafh.net), Stuttgart University of Applied Sciences, Schellingstr. 24, 70174 Stuttgart, Germany
Dirk Pietruschka: Centre for Sustainable Energy Technology (zafh.net), Stuttgart University of Applied Sciences, Schellingstr. 24, 70174 Stuttgart, Germany
Dietrich Schneider: Steinbeis-Innovationszentrum LOCASYS-Innovations, Osterholzallee 140-7, 71636 Ludwigsburg, Germany

Energies, 2021, vol. 14, issue 20, 1-29

Abstract: The volatility of renewable energy sources (RES) poses a growing problem for operation of electricity grids. In contrary, the necessary decarbonisation of sectors such as heat supply and transport requires a rapid expansion of RES. Load management in the context of power-to-heat systems can help to simultaneously couple the electricity and heat sectors and stabilise the electricity grid, thus enabling a higher share of RES. In addition power-to-hydrogen offers the possibility of long-term energy storage options. Within this work, we present a novel optimization approach for heat pump operation with the aim to counteract the volatility and enable a higher usage of RES. For this purpose, a detailed simulation model of buildings and their energy supply systems is created, calibrated and validated based on a plus energy settlement. Subsequently, the potential of optimized operation is determined with regard to PV and small wind turbine self-consumption. In addition, the potential of seasonal hydrogen storage is examined. The results show, that on a daily basis a 33% reduction of electricity demand from grid is possible. However, the average optimization potential is reduced significantly by prediction inaccuracy. The addition of a hydrogen system for seasonal energy storage basically eliminates the carbon dioxide emissions of the cluster. However, this comes at high carbon dioxide prevention costs of 1.76 € k g ?1 .

Keywords: demand response; demand side management; heat pump optimization; building simulation; HVAC optimization; genetic algorithm; heat pump cluster operation; demand flexibility; small wind turbine (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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