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.

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.

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.

Energy system modeling has been following the energy transition to investigate challenges and opportunities of future energy systems on all grid levels. Necessary input for sector-coupled energy system models are residential electricity and heat demand curves. The increasing importance of distribution grids and their modeling requires demand profiles in high spatial resolution.This paper presents a method to assign pre-generated electricity and heat demand curves to georeferenced residential buildings in Germany. We aim at overcoming fundamental shortcomings of the Standard Load Profiles and enable new possibilities for the modeling of distribution grids. Our approach provides a large variety in residential load profiles which spatially correspond to official socio-demographic data. All used input data sets as well as implemented methodology and the resulting profiles are publicly available under open source and open data licences to enable further use. Our results are validated on different aggregation levels as well as compared and discussed with the commonly used Standard Load Profiles.

In this paper five different flexibility options are analysed from a techno-economic perspective as alternatives to traditional grid expansion for a specific distribution grid in Germany. The options are: two reactive power control strategies with photovoltaic inverters (as a function of the power feed-in, or of the voltage at the connection point), one residential and two large scale battery storage applications (primary control reserve with autonomous reactive power control or self consumption maximisation strategy with autonomous reactive power control). For the pilot grid located in Southern Germany a photovoltaic expansion pathway is determined. The main goal of this work is to quantify the grid expansion actions that can be avoided by applying these five flexibility options for the assumed expansion pathway, focusing on large scale battery storages. It is shown that the five flexibility options increase the hosting capacity for PV systems, compared to a scenario without, by up to 45%. Furthermore, the results of the economic assessment indicate that the analysed flexibility options might be a viable alternative to traditional grid expansion as all of them show a cost reduction potential for the pilot region. These results could encourage DSOs to consider the integration of additional PV and battery storage systems not as a problem which triggers grid expansion, but as part of the solution reducing future grid expansion costs.

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.

Both global climate change and the decreasing cost of lithium-ion batteries are enablers of electric vehicles as an alternative form of transportation in the private sector. However, a high electric vehicle penetration in urban distribution grids leads to challenges, such as line over loading for the grid operator. In such a case installation of grid integrated storage systems represent an alternative to conventional grid reinforcement. This paper proposes a method of coordinated control for multiple battery energy storage systems located at electrical vehicle charging parks in a distribution grid using linear optimization in conjunction with time series modeling. The objective is to reduce the peak power at the point of common coupling in existing distribution grids with a high share of electric vehicles. An open source simulation tool has been developed that aims to couple a stand alone power flow model with a model of a stand alone battery energy storage system. This combination of previously disjointed tools enables more realistic simulation of the effects of storage systems in different operating modes on the distribution grid. Further information is derived from a detailed analysis of the storage system based on six key characteristics. The case study involves three charging parks with various sizes of coupled storage systems in a test grid in order to apply the developed method. By operating these storage systems using the coordinated control strategy, the maximum peak load can be reduced by 44.9%. The rise in peak load reduction increases linearly with small storage capacities, whereas saturation behavior can be observed above 800 kWh.

Primary control reserve and maximising self-consumption are currently two of the main applications for large-scale battery storage systems. Although being currently the most profitable application for large-scale batteries in Germany, storage systems applying primary control reserve have not been implemented in a grid supportive manner in distribution grids yet. Despite a current unfavourable regulatory framework and reimbursement scheme for community electricity storages in Germany, they are potentially more profitable than residential storages, which is mainly due to their economy of scale, and thus they may become the major large scale battery application in the future. The two applications: primary control reserve and maximising self-consumption, are combined with a grid supportive behaviour by providing reactive power control and/or peak shaving and are fitted to a vanadium redox flow battery prototype, which is installed in a distribution grid in southern Germany. Based on measured data from the prototype, two battery models for two different time resolutions (1s, 1min) are presented in detail along with their respective operation models. The operation strategy model for primary control reserve comprises the so-called degrees of freedom used to reduce the energy needed to recharge the battery. The operation strategy to maximise self-consumption is based on a persistence forecast. The model for the operation strategy for a grid supportive primary control reserve was validated in a field test revealing a relative error of 2.5 % between the simulated and measured state of charge of the battery for a multi-week time period. The technical assessment of both applications shows that the use of the degrees of freedom can reduce the energy to recharge the battery by 20 %; and in the case of self-consumption, the curtailment losses can be kept under 1 %. The economic assessment, however, indicates that even for the most promising primary control reserve case, the investment costs of vanadium redox flow batteries must be reduced by at least 30 % in order to break even. Finally, the encouraging key finding is that the negative impact of a grid supportive behaviour, additionally to its primary purpose, is less than 1 % of the revenues. This may encourage distribution grid and battery operators to consider the integration of large scale batteries in distribution grids as part of the solution of a rising share of a decentralised renewable energy generation.

The energy transition towards renewable and more distributed power production triggers the need for grid and storage expansion on all voltage levels. Today’s power system planning focuses on certain voltage levels or spatial resolutions. In this work we present an open source software tool eGo which is able to optimize grid and storage expansion throughout all voltage levels in a developed top-down approach. Operation and investment costs are minimized by applying a multi-period linear optimal power flow considering the grid infrastructure of the extra-high and high-voltage (380 to 110 kV) level. Hence, the common differentiation of transmission and distribution grid is partly dissolved, integrating the high-voltage level into the optimization problem. Consecutively, optimized curtailment and storage units are allocated in the medium voltage grid in order to lower medium and low voltage grid expansion needs, that are consequently determined. Here, heuristic optimization methods using the non-linear power flow were developed. Applying the tool on future scenarios we derived cost-efficient grid and storage expansion for all voltage levels in Germany. Due to the integrated approach, storage expansion and curtailment can significantly lower grid expansion costs in medium and low voltage grids and at the same time serve the optimal functioning of the overall system. Nevertheless, the cost-reducing effect for the whole of Germany was marginal. Instead, the consideration of realistic, spatially differentiated time series led to substantial overall savings.

In this article we apply the transparency checklist methodology by Cao et al. to a case study to evaluate the degree of transparency in energy system modelling. We use a recent case study conducted by the Reiner Lemoine Institut that analyses heat and electricity supply in a German region. An analysis of the questions of the transparency checklist indicates that different issues are addressed: transparency, reproducibility and quality. The completed checklist with answers regarding the case study and its supplementing materials shows that a large majority of the transparency (93%) and reproducibility criteria (73%) could be satisfied. However, only a smaller proportion (47%) of the questions categorised as quality criteria could be answered satisfyingly. A total of 31 out of 45 checklist questions are answered (69%). More than half (53%) of all questions were answered in the introduced framework, model and scenario fact sheets on the OpenEnergyPlatform. The gaps in answering the checklist (e.g., documenting assumptions, uncertainties, and validations) can be closed by an enhancement of the fact sheets and additional tools like the presented scenario log. We conclude that supplementing a final report or study with the presented fact sheets improves good scientific practice significantly while we identified existing weaknesses.

The rapidly increasing number of implemented photovoltaic (PV) systems in the German distribution grid in recent years has led to power quality issues due to the intermittent generation and reverse power flows in periods of low demand. In order to decrease this impact, different solutions are being investigated. The aim of this study is to analyze the maximum possible grid relief by using residential PV storage systems and different reactive power control strategies from the viewpoint of a distribution system owner. To compare the different voltage control method scenarios the hosting capacity is used as a performance indicator.