Efforts to decarbonise the transport sector lead to an increasing share of electric vehicles (EVs), which can impose significant stress on future distribution grids. The level of stress is thereby not only dependent on the number of integrated EVs but also the existing topology of the grid and present shares of supply and demand units. These factors are also likely to influence strategies to help the integration of EVs, such as utilising EV flexibility through smart charging. We therefore examine the influence of different charging strategies on distinct distribution grid types, namely PV-, wind- and load-dominated grids. With the help of a quadratic problem formulation including linearised AC power flow constraints, we deduce optimised charging profiles to minimise the additional stress on the grids. In reality, a central optimisation of all EVs might be challenging to implement. We therefore compare the results to rule-based charging strategies to extract suggestions for the effective integration of EVs. Our analysis shows that the potential of the examined charging strategies to decrease curtailment that is necessary to solve arising grid issues is limited. However, the additional grid expansion costs caused by EV integration, which mainly occur in the low voltage (LV), can be reduced significantly compared to the reference charging, where EV charging is mostly uncontrolled. Our results also show that the charging strategies prove to be differently useful in the different types of grids. This stresses the importance of considering various grid topologies when investigating the influence of smart charging on distribution grids.

Industrial Demand Response (IDR) presents a vital opportunity to enhance energy system flexibility, especially as the share of variable renewable energy continues to grow. Our paper studies the economic benefits of IDR in Finland's pulp and paper industry, which accounts for nearly half of the country's industrial electricity consumption. A load-shifting demand response model was developed using the open energy modelling framework (oemof) to represent the entire sector as a single flexible unit. The model simulates demand response participation across various electricity price scenarios and intervention periods, including stress scenarios based on the 2022 energy crisis. Our findings reveal that IDR can reduce peak electricity demand by up to 30 % and cut system costs for the industry by several million euros. Critically, DR's economic viability is profoundly amplified under high price volatility, relative cost reductions surged from 4 % with 2019 day-ahead prices to 7 % and 10 % with 2022 day-ahead and intraday prices, respectively. This substantial increase positions IDR as a financial resilience strategy during market stress. Furthermore, our analysis indicates that under extreme volatility, optimisation priorities shift towards holistic energy cost reduction rather than solely peak demand minimisation. Our work uniquely quantifies IDR's external economic amplification driven by acute market price volatility, providing empirical evidence of its immediate value. This distinguishes our work from existing literature that primarily focuses on internal operational constraints, specific production technology choices, or broad long-term system-level benefits. Despite limitations including deterministic modelling and industry aggregation, our study highlights the significant, yet untapped, potential for IDR in Finland's energy transition, underscoring the necessity of supportive policy and market incentives.

This paper investigates the potential of smart charging and vehicle-to-grid (V2G) to reduce the stress on German distribution grids. Specifically, two optimised charging strategies with respectively two levels of electric vehicle (EV) flexibility and reference charging are evaluated with respect to their potential to reduce the necessary curtailment and grid reinforcement and their flexibility potentials in terms of energy shifting. The levels of flexibility differ in three aspects. First, which charging use cases are assumed to be flexible. Second, if charging is only allowed within the originally scheduled charging session or between different parking events. And last, whether or not the V2G service is available. The reference strategy simulates uncoordinated charging. All optimised charging strategies successfully reduce the necessary curtailment by shifting the charging demand to times of high feed-in and lower component loading. Especially the curtailment of the load is significantly reduced by optimised charging, whereas the impact on the curtailment of feed-in is limited. The grid expansion costs are reduced by optimised charging, and peaks can be lowered. However, the additional gain from shifting between parking events and V2G is significantly smaller than the benefit from shifting within the originally scheduled charging session compared to reference charging. The available flexible energy, on the other hand, significantly increases with shifting between parking events and V2G. The added value of the different levels of EV flexibility therefore highly depends on the use case.

Dynamic tariff adoption is considered to be an important driver of demand response, enabling more sustainable and reliable power systems. However, first studies have shown that a high share of households subscribing to dynamic tariffs can lead to so-called "avalanche effects" on the distribution grid level, wherein load profiles align across households. Avalanche effects can create new demand peaks that necessitate costly grid reinforcement measures. Here, we analyze the impacts of policy options for grid charge and solar photovoltaic (PV) feed-in remuneration on grid reinforcement costs given increasing shares of dynamic tariff adoption. The analysis framework is open-source and uses empirical data from real households. We find that the widely proliferated regulatory scenario with volumetric grid charges and PV feed-in-tariffs leads to heavy reinforcement needs. We show that novel policy options, such as rotating or segmented grid charges, can alleviate grid reinforcement needs.

In a changing power system with increasing penetrations of distributed energy resources, traditional network tariffs might not be able to meet the underlying requirements. Therefore, it is necessary to assess suitable alternatives. We propose a new two-stage process and evaluation framework to support an informed decision process and test them in a Swiss environment. In the first stage, stakeholder interviews determine the relevant design criteria. In the second step, these are translated into a quantitative evaluation framework. The single indicators are weighted by expert weighting, following the analytic hierarchy process, to arrive at the final ranking. The application in a case study shows that the final ranking of the examined tariff structures depends on expert weighting. It is therefore vital to work on a shared understanding of the importance of the different criteria. Moreover, in a scenario with high shares of distributed energy resources, the volumetric tariff shows the lowest performance independent of expert weighting. This result stresses the importance of adapting network tariffs for a future power system with high penetrations of distributed energy sources. Our open-source evaluation tool can help with an informed and transparent decision process.

This paper investigates the potential of smart charging and vehicle to grid (V2G) to reduce the stress on German distribution grids. Therefore, two optimised and a reference charging strategy are evaluated with respect to their potential to reduce the necessary curtailment and grid reinforcement. Furthermore, the flexibility potential in terms of energy shifting is evaluated. The first optimised strategy, constrained charging, allows to shift charging demand only within standing times. The second optimised strategy, unconstrained charging, allows to shift charging demand over different charging events and to provide V2G service. The reference strategy simulates uncoordinated charging. Both of the optimised charging strategies successfully reduce the necessary curtailment by shifting the charging demand to times of high feed-in and lower component loading. Especially the curtailment of the load is significantly reduced by optimised charging, whereas the impact on the curtailment of feed-in is limited. The grid expansion costs are reduced by optimised charging, and peaks can be lowered. However, the additional gain from unconstrained optimised charging is significantly smaller than the benefit from constrained optimised compared to reference charging. The available flexible energy, on the other hand, increases by a factor of about nine with unconstrained charging compared to constrained charging. The added value therefore highly depends on the use case.

The increasing number of heat pump installations in Germany will require additional grid expansion and grid reinforcement measures. Grid operators call for measures to block heat pumps during critical, high load phases. However, the exact implementation of possible heat pump blocking periods and their impact on grid expansion costs remains unknown. This paper introduces a framework to evaluate the impact of heat pump blocking mechanisms on grid expansion cost, based on real-world household and heat pump load profiles. We show that previously suggested approaches in the literature, such as blocking all heat pumps in the grid during peak hours, lead to significant increases in distribution grid expansion costs due to catch-up effects. In addition, we introduce an open-source simulation model to assess the impact of heat pump blocking mechanisms on aggregated heat pump loads and peak loads at low computational costs.

The transition towards a renewable power grid raises various challenges in distribution grids, potentially leading to significant future reinforcement needs. This project analyses how different network tariffs can mitigate grid reinforcement by steering the use of decentralised flexibility options, namely curtailment of photovoltaic generation, battery storage systems, smart charging, and usage of thermal energy storage to shift heat demand. Therefore, the reaction of prosumers with different combinations of these flexibility options is modelled by a cost-minimising consumer-based optimisation. With these, a case study for six different grids in Germany is conducted for various combinations of different energy- and capacity-based tariff components. The analysis shows that time-varying energy-based components such as a day/night energy tariff or time-varying suppliers' cost lead to a synchronisation of the flexibility options. This synchronisation can increase grid reinforcement costs, depending on the penetration of flexibility options and the user preference. On the other hand, capacity-based tariff components on peak load and feed-in generally reduce the costs. However, these components can also reduce synergies between closely located users in specific situations. Overall, the tariff with a constant energy component and capacity components on peak load and feed-in shows the highest potential to reduce the reinforcement costs, showing a reduction of 9.5% in all the investigated grids.

With increasing penetrations of distributed energy resources (DERs) introduced to the distribution grids (DGs), these grids will require reinforcements. This study analyses the required grid reinforcement costs for six medium voltage (MV)-grids with underlying low voltage (LV)-grids and different characteristics to provide an estimate of the required costs and evaluate the cost reduction potential by utilising flexibility from the DERs. Therefore, increasing penetrations of photovoltaic (PV), battery energy storage systems (BESS), heat pumps (HPs) and electric vehicles (EVs) are added to residential loads of the grids. To quantify the cost reduction potential, the required grid reinforcement is determined for a reference and an optimised operation of the DERs. The results show that integrating HPs leads to the highest marginal and absolute costs and that HPs are the main driver of the costs when all DERs are integrated simultaneously. The optimised operation of the DERs can reduce the grid reinforcement costs for all simulated scenarios. However, the extent to which the grid reinforcement can be reduced differs. For home charging of EVs, grid reinforcement can be nearly completely avoided with the optimised operation. For PV with BESS and HPs, reductions of 45.2% and 13.6% at a 100% penetration can be achieved, respectively. When all types of DERs are integrated simultaneously, it is possible to decrease the costs by 23.6% with the optimised operation.

The ongoing energy transition introduces new challenges for distribution networks and brings about the need to expand existing power grid capacities. In order to contain network expansion and with it economic costs, utilization of various flexibility options to reduce expansion needs is discussed. This paper proposes a multiperiod optimal power flow (MPOPF) approach with a new continuous network expansion formulation to optimize the deployment of flexibility options under the objective of minimizing network expansion costs. In a comparison of the newly proposed continuous network expansion formulation with an existing mixed integer formulation and a continuous interpretation of the latter the here proposed formulation is shown to be useful in order to obtain a solvable problem and contain computational efforts. The presented MPOPF including the flexibility options storage units and curtailment is then assessed on synthetic medium voltage grids and applied to evaluate the benefit of a combined vs. a stepwise optimization of these flexibility options. It is demonstrated that using a local solver the proposed approach is applicable and yields a solution in reasonable time. Furthermore, it is shown that the combined optimization generally leads to a more efficient utilization of the considered flexibility options and therefore lower grid expansion costs than the stepwise consideration.

To reach climate targets, future energy systems must rely heavily on variable renewable energy sources (VRES) such as wind and photovoltaic (PV). As the share of VRES increases, the topics of flexibility and the smart interplay of different flexibility options grow in importance. One way to analyse flexibility options and enhance the design of future energy systems is to use energy system modelling tools. Although a wide range of openly accessible models exist, there is no clear evaluation of how flexibility is represented in these tools. To bridge this gap, this paper extracts the key factors of flexibility representation and introduces a new classification for flexibility and influencing factors. To evaluate the current modelling landscape, a survey was sent to developers of open energy modelling tools and analysed with the newly introduced Open ESM Flexibility Evaluation Tool (OpFEl), an open source evaluation algorithm to assess the representation of different flexibility options in the tools. The results show a wide range of different tools covering most aspects of flexibility. A trend towards including sector coupling elements is visible. However, storage and network type flexibility, as well as aspects touching system operations, are still underrepresented in current models and should be included in more detail. No single model covers all categories of flexibility options to a high degree, but a combination of different models through soft coupling could serve as the basis for a holistic flexibility assessment. This, in turn, would allow for a detailed evaluation of energy systems based on VRES.

Market-oriented charging, based on real-time electricity prices, was in a previous study shown to benefit the integration of variable renewable energy sources (VRES) by significantly reducing market-driven curtailment. In this study, we assess the impact of market-oriented charging of electric vehicles (EVs) on medium-voltage (MV) and low-voltage (LV) grids in Germany and compare it to an uncoordinated charging. The analyses are conducted on synthetic grid topologies for a 2030 scenario with 10 million passenger cars. We show that market-oriented charging has different effects on the assessed grid types. In photovoltaics (PV)- and winddominated grids, as well as load-dominated suburban and rural grids, a minor increase in load-driven grid issues is observed, predominantly due to wind-feed-in driven charging peaks in the winter. Feed-in curtailment, however, is slightly reduced, which can mainly be attributed to a reduction of PV curtailment. In urban grids, on the other hand, market-oriented charging results in a significant increase in the number and degree of load-driven grid issues. As urban grids only make up around 7% of German MV grids, the impact for entire Germany is found to be moderate. Assuming load-driven grid issues could be solved by a curtailment of charging demand, it is found that marketoriented charging results in an increased curtailment of only 0.7% of the total charging demand. A sufficiently high benefit in overlaying grid levels could thus outweigh the drawback of increased stress on urban grids.

This work investigates the power sharing of distributed energy resources, such as diesel synchronous generators and inverter-coupled batteries, in islanded microgrids after load transients. Firstly, the necessary accuracy of the diesel synchronous generator model for dynamic simulation and small signal stability studies is examined. Secondly, the controller parameters are optimized deploying a genetic algorithm to enhance the transient load sharing between synchronous generators and battery inverters.