@article{65757,
  abstract     = {{Electrifying the heating sector is essential for achieving global climate targets like the Paris Agreement’s 1.5 °C goal. In Germany, where 80  % of household energy goes to space heating and hot water, shifting to low-carbon solutions is crucial. Fossil-fuelled district heating networks can incorporate renewable energy via heat pumps, improving efficiency. Although heat pump design typically favours minimal temperature lifts, higher lifts can be economically viable with low electricity prices and abundant renewables. Adding thermal energy storage boosts operational flexibility. This study explores a flexible heat pump operation incorporating part load behaviour with a thermal energy storage in a German city’s district heating system to minimise costs and carbon dioxide emissions. Using a mixed-integer linear programming model, it examines the impact of temperature adjustments and storage on system efficiency. The results show that the integration of a heat pump in a district heating system reduces operating costs. Compared to a supply without a heat pump, with levelised cost of heating of 9.98 cent/kWhth and a fixed operating mode with costs between 9.96 cent/kWhth and 11.49 cent/kWhth, the flexible use results in lowest costs of 9.85 cent/kWhth, while also reducing overall CO2 emissions. Using a full factorial sensitivity analysis, the levelised cost of heating ranged between 9.15 cent/kWhth in the best case and 10.37 cent/kWhth in the worst case for the selected configuration.}},
  author       = {{Rahlf, Henning Christoph and Divkovic, Denis and Knorr, Lukas and Schlosser, Florian and Meschede, Henning}},
  issn         = {{0196-8904}},
  journal      = {{Energy Conversion and Management}},
  keywords     = {{Heat transition, Optimisation, Temperature flexibility, Decarbonisation, Multi energy}},
  publisher    = {{Elsevier BV}},
  title        = {{{Flexible operation strategies for heat pumps in district heating systems using dynamic electricity prices}}},
  doi          = {{10.1016/j.enconman.2026.121714}},
  volume       = {{364}},
  year         = {{2026}},
}

@article{63838,
  abstract     = {{Industrial electrification is increasing to reduce fossil fuel dependence, alongside a growing share of volatile renewables.
A secure and reliable energy supply is crucial for industry, leading to a shift from centralised to decentralised grid structures.
DC microgrids becoming increasingly popular in industry, since they enable energy recuperation from braking, reduce components and cables, and integrate storage and local generation to manage supply interruptions or peak loads.
EVs add further synergies by serving as mobile storage units, helping to store and redistribute locally generated renewable energy.
This paper analyses how EV integration in droop-controlled DC grids can contribute to a more stable, low-emission and peak-reduced load profile to the supply grid through load shifting and bridge interruptions.
A droop-controlled DC grid model has been developed, incorporating an EV charging park based on probability functions.
Scalable scenarios allow for diverse condition analysis using an energy management system that utilises fuzzy logic and sequential MILP optimisation.
It has been shown that a 7% improvement of coefficient represented grid-serving behaviour is possible by load shifting.
It has also been demonstrated that an optimised EMS can reduce the demand-based CO2 emissions by 41kg for a representative day compared to a fuzzy logic EMS.
At the same time peak load is decreased yielding a more constant residual load.
These results highlight the potential of a controlled bidirectional charging infrastructure in DC grids and underscore the need to explicitly consider charging processes to ensure a residual load as constant as possible.}},
  author       = {{Rahlf, Henning Christoph and Knorr, Lukas and Althoff, Simon and Meschede, Henning}},
  issn         = {{2666-9552}},
  journal      = {{Smart Energy}},
  keywords     = {{DC-grid, Droop control, Grid-serving behaviour, Grid stability, Bidirectional charging, Sequential decision, MILP optimisation}},
  publisher    = {{Elsevier BV}},
  title        = {{{Analysis of bidirectional EV charging infrastructures within industrial DC grids}}},
  doi          = {{10.1016/j.segy.2026.100227}},
  year         = {{2026}},
}

@article{66001,
  abstract     = {{Expanding renewable energy sources is essential for a sustainable energy supply but challenges grid stability, as the volatility of solar and wind causes periods of over- and undersupply. Private households are central to this transition, combining dynamic consumption with decentralised generation. This paper presents a multi-agent microgrid simulation built on the Mesa framework, focusing on the heterogeneous objectives and technological capabilities of residential participants. Households are modelled as autonomous agents with individual strategies, while a dedicated “grid agent” represents the distribution system operator and regulates the microgrid in a grid-supportive manner. The emission factor serves as the key indicator for grid-friendly behaviour. Results show that in summer, unmanaged PV feed-in from heterogeneous households causes substantial grid stress and balancing effort for the distribution system operator. Dynamic electricity prices can incentivise grid-friendly dispatch, but their effectiveness depends on the correlation between price signals and renewable availability and cannot guarantee grid-supportive behaviour alone. The grid agent reliably improves the grid-supportive coefficient, yet its operating strategy, for instance additional peak-reduction objectives, can interfere with price-based incentives. Effective demand-side management therefore requires careful analysis of stakeholder interactions. Building on this insight, thepaper provides a basic framework for the design, implementation, and assessment of both integrated and individual energy management strategies within a microgrid environment. By simulating the dynamic interactions among system participants and strategies, it enables comprehensive evaluation of their collective impact on the grid, supporting the development of robust solutions for future electricity networks.}},
  author       = {{Henne, Kevin and Rahlf, Henning Christoph and Naumann, Marius and Meschede, Henning}},
  issn         = {{2590-1745}},
  journal      = {{Energy Conversion and Management: X}},
  keywords     = {{Microgrid, Decentralised Energy Systems, Multi-Agent System, Residential Demand-Side Management, Optimisation}},
  location     = {{Dubrovnik}},
  pages        = {{102030}},
  publisher    = {{Elsevier}},
  title        = {{{Towards Stakeholder-Aware Demand-Side management assessment in heterogeneous residential Microgrids: A Multi-Agent approach}}},
  doi          = {{https://doi.org/10.1016/j.ecmx.2026.102030}},
  volume       = {{31}},
  year         = {{2026}},
}

@misc{60086,
  author       = {{Divkovic, Denis and Kirschbaum, Julia and Rahlf, Henning Christoph and Knorr, Lukas and Meschede, Henning}},
  publisher    = {{International Conference on Smart Energy Systems}},
  title        = {{{Optimising Heat Planning: Cost effective heat planning for low carbon district heating}}},
  year         = {{2024}},
}