Conference Agenda

The integrated simulation and optimization of various energy sectors - electricity, gas, heat, and transportation - will significantly advance Germany's energy system development, particularly at the regional level.

We introduce a time-expanded holistic optimization model for sector coupling, aimed at minimizing operational expenditures through strategies such as bidirectional electric vehicle charging and optimal control of heat pumps and electrolyzers. To address scalability challenges, we employ the rolling horizon approach as a decomposition method and primal heuristic, demonstrating its effectiveness in optimizing complex energy systems.

Through a case study using the example of the county Bayreuth as part of the research project 'ESM-Regio', we showcase the substantial potential of sector coupling in achieving Germany's 2045 renewable energy targets.

In future energy systems, flexible resources will play a key role. Especially the increasing flexible demand in home energy systems will present challenges for the distribution grid, but it will also provide opportunities to manage problems like grid congestions. In this work, a flexibility band is defined which gives information about the load flexibility of households, which can be used by higher-level actors like grid operators or energy aggregators. The basis is given by a load trajectory of a household without external influences, which accounts for the habitants’ different needs like room heating or charging of electric vehicles. A grid operator or aggregator can influence the household to change its planned load trajectory by providing an external signal, e.g. a direct intervention or a price signal. With the flexibility band, the maximum possible deviation between the reference and other load trajectories is determined which avoids compromising the habitants’ comfort. Consequently, the provider of the external signal can anticipate the respective effect. While previous studies of flexibility bands rely on the exchange of state information from both, household and grid operator, here the goal is to reduce the interaction that is required by providing a corridor in which all trajectories are feasible for the home energy system. To achieve this aim, a MILP modelling concept is presented which allows to calculate the flexibility band. First results and present and future challenges are discussed as well.

With rising sales of electric vehicles and increasing renewable energy generation, the existing electricity grid faces challenges from both the supply and demand sides. Increased renewable energy generation leads to higher volatility in production, resulting in a greater need for balancing energy. Moreover, the growing number of electric vehicles on the roads increases the demand for power, especially for fast charging at public stations.

Vehicle-to-grid (V2G) is a promising concept that intelligently manages the charging processes of electric vehicles to benefit the grid and support the integration of higher levels of volatile renewable energy. Part of the grid-connected battery capacity could be offered to the balancing energy market. To facilitate this, vehicle owners might use an aggregator service to simplify market access. This aggregator not only supplies charging stations with power sourced from the general electricity markets but also sells storage capacity and the potential to feed energy back into the grid in the balancing energy market, thus acting on different energy markets.

The aggregator aims to optimise its operation under given market conditions. This work presents an approach for integrating a vehicle-to-grid aggregator into energy market complementarity models as a market-coupling entity. In addition, a preliminary study on how market equilibria are affected under these circumstances is provided.