Effects of the tenants electricity law on energy system layout and landlord-tenant relationship in a multi-family building in Germany

Multi-family buildings (MFB) accommodate 53% of the German apartment stock. Although PV-systems on single-family buildings are widely implemented, the PV-potential on MFBs has barely been touched. Therefore, the German government introduced the Mieterstromgesetz, the tenants electricity law (TEL), in 2016. This law exempts electricity directly produced and consumed in a building from certain charges and taxes. Within the TEL framework, the landlord acts as the local electricity provider and can profit from selling electricity to the tenants and tenants can save electricity costs. This paper analyses the techno-economic effects of the TEL on the energy system layout of a MFB in Germany. Furthermore, it gives implications on how the TEL affects the tenant-landlord relationship. In this analyses, a MILP model is used to maximize the net present value (NPV) and determines the optimal layout and dispatch of the energy system. The model can choose to invest in PV, CHP and a battery storage system. Additionally, one to six electric vehicles (EVs) are integrated into the model. The novelty of this paper is the model-based analysis of the German Mieterstromgesetz considering EVs. The results show that the combination of PV and CHP is the most profitable system layout with NPVs up to 31.9ke. An optimized charging strategy increases the self-consumption rate and the NPV substantially compared to a fast-charging-strategy. Thus, the TEL can create a symbiotic relationship between landlords and tenants

The impact of public acceptance on cost efficiency and environmental sustainability in decentralized energy systems

Funding Information: The authors would like to thank H.G. Schwarz-von Raumer as well as the German Federal Agency for Nature Conservation for providing the scenicness data. Large parts of the methodology of this study were developed during the first author's three-and-a-half year PhD study period. The first author would therefore like to thank the three funding bodies during this period: the German Federal Ministry of Education and Research (BMBF) within the Kopernikus Project ENSURE “New ENergy grid StructURes for the German Energiewende” (funding reference: FKZ 03SFK1N0 ), the PhD College “Energy and Resource Efficiency” ( ENRES ) from the Federal State of Baden-Wuerttemberg, as well as the German Federal Ministry for Economic Affairs and Energy (BMWi) within the TrafoKommune project (funding reference: 03EN3008F ).Peer reviewedPublisher PD

Optimal system design for energy communities in multi-family buildings : the case of the German Tenant Electricity Law

Funding Information: The second author (MK) appreciates the support of the Helmholtz Association under the Joint Initiative Energy Systems Integration (funding reference: ZT-0002 ). The fourth author (FS) kindly acknowledges the financial support of the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement no. 713683 (COFUNDfellowsDTU). The fifth author (RM) gratefully acknowledges the support of the European Commission’s DG ENER for project ENER/C3/2019-487 . Finally, the authors are grateful for the helpful comments of two anonymous reviewers during earlier revisions of this manuscript. The usual disclaimer applies. Funding Information: The second author (MK) appreciates the support of the Helmholtz Association under the Joint Initiative Energy Systems Integration (funding reference: ZT-0002). The fourth author (FS) kindly acknowledges the financial support of the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement no. 713683 (COFUNDfellowsDTU). The fifth author (RM) gratefully acknowledges the support of the European Commission's DG ENER for project ENER/C3/2019-487. Finally, the authors are grateful for the helpful comments of two anonymous reviewers during earlier revisions of this manuscript. The usual disclaimer applies. Publisher Copyright: © 2021 Elsevier LtdPeer reviewedPostprin

Exploring socioeconomic and temporal characteristics of British and German residential energy demand

The British and German residential sectors account for similar fractions of national energy demand and carbon emissions. They also exhibit underlying differences in the building stock, fuel split, tenure and household load profiles. The temporal habits in British and German households are also quite different, which is challenging to measure due to the paucity of German smart meter data. This contribution takes this background as a starting point to explore some of the temporal and socioeconomic characteristics of residential energy demand in Britain and Germany. The Centre for Renewable Energy Systems Technology (CREST) residential load profile generator is updated for the UK and extended to the German context and validated with standard load profiles, providing high levels of accuracy according standard normalized root-mean-squared error (NRMSE) measures. The paper then analyzes the energy-related activities of different socioeconomic household groups based on with National Time Use Survey data from both countries. The analysis showed some clear differences between groups and countries, which are a reminder of the importance of non-energy policy (e.g. school hours) in determining peaks. As well as encountering useful insights into international differences in energy related behaviour, the results showed some key differences within specific socioeconomic groups, such as single persons, families with children, and pensioners. Further work will focus on extending the German CREST model to include a German appliance stock, as well as allocating these appliances according to households’ socioeconomic characteristics. The definition of the groups themselves needs to be refined, perhaps to include multiple variables and based on clustering or similar techniques, and validation with smart meter data

Identification of potential off-grid municipalities with 100% renewable energy supply

An increasing number of municipalities are striving for energy autonomy. This study determines in which municipalities and at what additional cost energy autonomy is feasible for a case study of Germany. An existing municipal energy system optimization model is extended to include the personal transport, industrial and commercial sectors. A machine learning approach identifies a regression model among 19 methods, which is best suited for the transfer of individual optimization results to all municipalities. The resulting levelized cost of energy (LCOE) from the optimization of 15 case studies are transferred using a stepwise linear regression model. The regression model shows a mean absolute percentage error of 12.5%. The study demonstrates that energy autonomy is technically feasible in 6,314 (56%) municipalities. Thereby, the LCOEs increase in the autonomous case on average by 0.41 €/kWh compared to the minimum cost scenario. Apart from energy demand, base-load-capable bioenergy and deep geothermal energy appear to have the greatest influence on the LCOEs. This study represents a starting point for defining possible scenarios in studies of future national energy system or transmission grid expansion planning, which for the first time consider completely energy autonomous municipalities

Optimal Renewable Energy Based Supply Systems for Self-sufficient Residential Buildings

To cover 100% of the energy demand using renewable energies, technologies like small wind turbines (SWT) or hydrogen (H2) storage systems could be integrated into the household energy system. In this study optimal self-sufficient energy supply systems for residential buildings are determined using an MILP optimization model. To consume energy at the time it is generated, flexible devices and optimal charging strategies for electric vehicles are considered. Least cost systems for different regions are identified and compared to a conventional reference system. It is shown that H2 storage systems and SWT can be economically beneficial for self-sufficient household supply

Developing a three-stage heuristic to design geothermal-based district heating systems

Geothermal plants have been increasingly constructed in recent years to exploit the high geothermal energy potential in Germany in district heating networks at the municipal level. In order to use this potential economically, municipal planners need instruments for designing the district heating network to supply households with the geothermal heat. This paper presents a combinatorial mixed-integer linear optimisation model and a three-stage heuristic to determine the minimum costs for geothermal district heating systems in municipalities. The central innovations are the ability to optimise both the structure of the district heating network and the location of the district heating plant, the consideration of partial heat supply from district heating and the scalability to many larger municipalities. A comparison of optimisation and heuristic for three exemplary municipalities demonstrates the efficiency of the developed heuristic: the optimisation takes between 500% and 10,000,000% more time than the heuristic. The resulting deviations in the calculated total investment for the district heating from the results of the optimisation are in all cases below 5% and in 80% of cases below 0.3%. The efficiency of the heuristic is further demonstrated by the comparison with simpler heuristics like the Nearest-Neighbour-Heuristic. The latter is not only less efficient, it substantially overestimates the total costs by up to 80% in all cases with less than 100% heat coverage. Future work should focus on a more precise consideration of heat losses in the district heating network, as well as taking additional geological and topological conditions in the municipalities into account