The transformation to a climate-neutral energy supply leads to a structural change to a converter-dominated grid. The shutdown of fossil power plants causes a demand for grid inertia from renewable energy sources, previously provided exclusively by synchronous generators. Not only generation plants but also controllable loads can contribute to grid inertia or dynamic fre-quency stability, depending on hardware requirements, the control concept, and the dynamic flexibility of the plant process. The need for hydrogen expands electrolyzers on a gigawatt scale and offers the potential to use the plants in a grid-serving mode to ensure transient grid stability. The paper addresses the research question of which time range the dynamic flexibility of electro-lyzers must be from the grid point of view. In order to investigate this, a megawatt-scale living-lab is introduced. Subsequently, the basics of grid stability, future stability challenges, and how this can be supported by the use of grid-forming and grid-supporting electrolysis converters are discussed. It is shown that grid-forming controlled electrolyzers must be able to adjust their power within approx. 0,4 s to provide inertia. As far as this can be realized, it offers a large potential for securing grid stability in future.

The increasing installed capacity of renewable energy systems is changing the traditional supply of ancillary services by displacing synchronous generators. On the one hand, this creates the need to develop alternative sources, on the other hand, it also opens up opportunities for flexible and cost-efficient solutions. Against this background, this paper investigates the future role of renewable energy resources in the context of reactive power management using a simulation model of a real German high-voltage grid. Both the potentials of reactive power provision in the high-voltage grid and different strategies for reactive power control are analysed. In addition to conventional characteristic driven controls, an optimisation-based approach using the particle swarm optimisation is also considered. The simulation results underline the considerable potential increases through an extension of the operating ranges of renewable energy plants. Furthermore, it is shown that optimised use of these sources can improve grid stability and reduce overall system costs. In this context, optimised operation can have advantages for both the grid operator and the operator of the renewable energy system.

Electric vehicles can be charged on many occasions along the daily route of the electric car driver. The driver of an electric car has many different opportunities to charge his vehicle, e.g. at home,in the company, at shopping malls or on motorways / traffic axes. Depending on the charging use case, different stakeholders are involved along the energy industry value chain, starting with energy generation, energy supply, energy distribution and energy consumption. The resulting multiple compositions and dependencies can be represented in the Electric Vehicle Charging Journey Architecture Model. A main focus is on the distance to be covered by the EV driver. The charging journey is derived from the starting point and destination of a driven distance, which implies that the vehicle can be charged at least at one of the two given endpoints. A common charging journey is charging at home and in the company. The aim of this research work is to analyse the charging journey home - company on the basis of case studies with companies from different sectors which have different energy-economic and technical framework conditions. In a simulation with Python, the real charging processes of the electric car drivers in the company are examined with real load profile data of the infrastructure. A survey among the participants of the case study regarding the energy-economic and technical framework conditions at home as well as the personal preferences for the charging behaviour provides real data for the starting point of the charging journey. From this aggregated data of both endpoints of the charging journey, application preference, operational preference and timetable preference within all stakeholders of the energy value chain are derived. By shifting the charging processes between the two endpoints, the preferences can be maximised. In this way, an overall energy and technoeconomic optimum can be named in a benchmark process in order to efficiently design the further expansion of electromobility for the investigated charging journey.

In a field test related to the project LISA4CL charging processes and load profiles of the infrastructure were measured. This paper analyses the results of the field test. The charging processes are evaluated on different aspects such as simultaneity factor, CO2 footprint, energy costs, demand power and self-consumption of a photovoltaic power plant. Based on the data from the field test, different smart charging strategies are analyzed. The results from the smart charging strategies are compared to the actual charging processes. Key findings of this research are the possible adjustments of the charging process and the possible reduction of the peak load. The results show that all priced-based methods led to a high simultaneity of charging processes. A maximum available grid power for the infrastructure can reduce the peak load. In case of variable energy prices, the limitation of the grid power can lead to higher costs for the charging process itself but can reduce the peak load. In the end, the reduction of the power leads to an overall cost reduction for the infrastructure operator if considering power-based fees. With the integration of photovoltaic power plant, the C02 footprint can be reduced. This can also lead to lower costs of electricity. Most of the charging processes were done overnight, which reduces the advantages of a photovoltaic power plant.

Battery-electric mobility represents the most promising post-fossil mobility approach as the number of electric vehicles (EVs) worldwide has grown exponentially in recent years. However, the increased electricity demand resulting from EVs' charging processes was unknown when planning the electric grid of existing districts and nowadays may cause violations of operational boundaries. This paper presents an open-source co-simulation using MOSAIK 3.0 to analyze the effects and impacts of an increasing EV penetration rate on the low-voltage grid. The co-simulation is applied to the existing residential district “Am Ölper Berge” in Brunswick, Germany. Within multiple scenarios, user-sided measures for cooperative energy generation, storage, and smart charging strategies are applied to enhance the grid's capacity for EVs by improving voltage regulation. The most effective measure enhancing grid capacity is the self-developed grid correction model, which mitigates voltage range violations using the flexibility of the district's battery storage systems. Solely adding user-sided measures does not create synergistic effects for the grid integration of EVs. Instead, the smart charging strategies enable exploiting these synergies leading to a significant increase in grid capacity. The extendable co-simulation, including the energy system models, simulation scenarios, and input data, will be publicly available and can thus be used for further research.

The first variable electricity tariffs to charge electric vehicles are offered. Variable electricity tariffs for electric vehicle charging can lead to high simultaneity of charging because each user wants to charge at the times when electricity costs are low. This charging behaviour can stress the distribution grid because, for example, peak loads and overloading of grid components can occur. In addition, this effect is enhanced by similar user behaviour in terms of electric vehicle usage times and standing times. The shifting of charging processes and the consideration of grid loads in the variable tariffs are suitable methods in order to reduce grid overloading. In this paper, different price models for different transmission zones in Germany are introduced. Based on these prices, the charging times at the lowest cost are calculated. The usage times and standing times of the battery electric vehicle are equal for all calculations. It is assumed that the battery electric vehicle is charged overnight. Subsequently, the different charging times are compared. It is shown that different charging times for the different price models occur. However, the resulting prices for charging do not reflect the real cost of the electricity consumption with a variable electricity tariff. Therefore, the real cost of charging is compared to the lowest possible cost during the considered standing period. A possible solution to reduce these price differences is the reduction or increase of grid fees These pricing models can reduce the simultaneity of charging processes. Furthermore, it is planned to evaluate the impact of these charging times on the grid as part of the field test related to the LISA4CL project.

To counteract a potential reduction in grid stability caused by a rapidly growing share of intermittent renewable energy sources within our electrical grids, large scale deployment of energy storage will become indispensable. Pumped hydro storage is widely regarded as the most cost-effective option for this. However, its application is traditionally limited to certain topographic features. Expanding its operating range to low-head scenarios could unlock the potential of widespread deployment in regions where so far it has not yet been feasible. This review aims at giving a multi-disciplinary insight on technologies that are applicable for low-head (2-30 m) pumped hydro storage, in terms of design, grid integration, control, and modelling. A general overview and the historical development of pumped hydro storage are presented and trends for further innovation and a shift towards application in low-head scenarios are identified. Key drivers for future deployment and the technological and economic challenges to do so are discussed. Based on these challenges, technologies in the field of pumped hydro storage are reviewed and specifically analysed regarding their fitness for low-head application. This is done for pump and turbine design and configuration, electric machines and control, as well as modelling. Further aspects regarding grid integration are discussed. Among conventional machines, it is found that, for high-flow low-head application, axial flow pump-turbines with variable speed drives are the most suitable. Machines such as Archimedes screws, counter-rotating and rotary positive displacement reversible pump-turbines have potential to emerge as innovative solutions. Coupled axial flux permanent magnet synchronous motor-generators are the most promising electric machines. To ensure grid stability, grid-forming control alongside bulk energy storage with capabilities of providing synthetic inertia next to other ancillary services are required.

The urgent need to reduce carbon emissions resulting in decentralized renewable energy systems also encourages the establishment of energy communities where residential and/or commercial consumers can actively participate in the generation, consumption, or provision of flexibility of electric energy. The integration of electric mobility within these energy communities is of particular interest as ...