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As part of transmission network expansion planning (TNEP), a technical and economical assessment of several planning alternatives must be performed in order to ensure fulfillment of the network security criteria and to estimate the alternatives’ expected operating costs. This task requires performing load flow calculations for different operating points (OPs) of the power system. Due to the high computational burden, considering all possible OPs is simply not possible. As a consequence, only a set of representative OPs is usually taken into account. Most works in the TNEP focus on issues related to optimization algorithms and modeling, neglecting the selection process of the representative OPs. Furthermore, most works only consider a few OPs, providing little or no insight about the criteria used in the selection process or about the error made when evaluating planning alternatives using a limited number of OPs. In this work, a novel methodology for selecting representative OPs to consider within the TNEP is presented. The proposal pays special attention to critical situations, where the network security may be endangered. Furthermore, the methodology allows quantifying the error made when evaluating network operation using a limited number of representative OPs. [ABSTRACT FROM AUTHOR]

Advances in medium voltage direct current (MVDC) technologies and the penetration of extended MVDC systems are still significantly hindered by the lack of adequate direct current (DC) switching equipment. The fundamentally different fault current behavior in case of a DC fault, compared to faults in alternating current (AC) systems, with regard to the characteristics and development of fault currents and their interruption make dedicated test procedures necessary. One testing approach is the application of a power-electronic buck converter (PEBC) to simulate relevant stresses on DC switching equipment during a DC fault current interruption. Since the associated requirements, especially regarding current ratings of several kiloamperes, cannot be fulfilled by using a singular PEBC, a modularization becomes necessary. However, particularly in high-power applications, the interconnection of several PEBC modules poses significant challenges. In this article, a demonstrator PEBC-based high-power test circuit for the provision of relevant testing parameters is presented. The underlying challenges and respective solutions with regard to the interconnection of, in total, 120 individual PEBC modules are discussed. It can be shown that the harmonization of connection busbar inductances is the main contributor towards a stable and safe test circuit operation. [ABSTRACT FROM AUTHOR]

Foam-based internal electrical insulation of hollow-core composite insulators (HCIs) is regarded as a superior solution to gases for not requiring continuous monitoring, with polyurethanes (PUs) being the main solution to date. Potential restrictions facing PUs as well as the need for higher dielectric strengths have prompted research activities into alternative foams. This work follows an extensive experimental and simulative approach to investigate the dielectric strength of a novel polymeric foam, known as dry syntactic foam (DSF). Seven different densities in two thicknesses are manufactured and tested under ac, dc, and lightning impulse (LI) voltages. Two finite-element (FE) models are created based on microscope images to reproduce electrostatic- and conduction-dominated voltage distributions and complement the experiments. Under ac and LI, the dielectric strength is found to rise with foam density, whereas no distinctive effect is observed under dc stress. The simulations indicate that under ac and LI, the highest electrical fields are reached uniformly inside gas pores and, that under dc, certainly arranged pores observe significant higher stresses. The ac and LI results are discussed according to Townsend discharges, whereas a mechanism based on a transient process is suggested for dc. [ABSTRACT FROM AUTHOR]

Grid integrated water electrolysers have the potential of coupling electric power systems subjected to high shares of renewable energy sources with sectors of hydrogen demand, thus contributing to European decarbonization goals in future. We therefore investigate the business potential of future electrolyser applications in cross-commodity arbitrage trading by applying a complex power market simulation method for future scenarios and different European countries. Based on this, we evaluate the potential of additional provision of grid services towards grid operators in order to increase the electrolyser utilization ratio. For this, we use a method that identifies measures of transmission grid operators in order to ensure secure grid operation. In this context, uncertain hydrogen prices and different sectors of hydrogen demand are addressed through sensitivities of different hydrogen sales prices. The analysis shows a high dependency of business model efficiency on the hydrogen price. While cross-commodity arbitrage trading can achieve profitability for the transportation sector, applications for the industry sector and natural gas system are less efficient. The results however indicate that for these less efficient applications grid service provision can be an option of increasing the electrolyser utilization ratio thus increasing its profitability. [ABSTRACT FROM AUTHOR]

For future multi‐terminal HVDC networks, protection systems based on DC circuit breakers (DCCBs) are envisioned to limit the loss of power transmission towards AC grid(s). Yet, HVDC protection system design is considered a major challenge—especially in a multi‐vendor setup. In particular, protection systems shall enable HVDC converters to ride through DC faults without protective blocking. Several studies have performed sensitivity analyses to determine the DCCB properties and current‐limiting inductor properties that are required to enable converter fault‐ride‐through (FRT), but the HVDC converters themselves have been simplified and kept identical. However, in a multi‐vendor setup, the exact converter design is not known at the time of DC protection planning. Therefore, this paper investigates the impact of different converter properties on the DC‐FRT behaviour, and reveals implications on HVDC protection design. Firstly, analytical approaches are proposed to mathematically derive potential impact factors on the converters' FRT characteristics, also considering different converter control architectures. Secondly, a comprehensive EMT study demonstrates a significant impact of the converter parameters on the FRT behaviour. Analytical approaches and EMT results are compared with regard to limitations and applicability, such that the paper's findings can support the development of functional requirements for multi‐vendor multi‐terminal HVDC networks. [ABSTRACT FROM AUTHOR]

National climate protection goals require the emission reduction in municipal energy supply systems. Those systems include energy conversion units like heatings, energy storages, and grids for electricity, gas, and heat. This paper presents a mixed-integer linear optimization model for the integrated and multi-modal planning of such municipal energy systems to reach a defined CO 2 emission limit with the least-cost system design. The exemplary application of the model to a study case with 3900 buildings shows that the flexible hybrid energy system resulting without emission restrictions gradually transforms into an inflexible system solely relying on pellet heaters and photovoltaic units when tightening the emission limit by just a few percentage points. • Integrated and multi-modal design conception for municipal energy supply systems. • Optimization of energy conversion units, storages, and electric, heat, and gas grid. • Binary grid investment decisions, energy storages, and two-stage optimization added. • Economically optimal system combines multi-valent central and decentral supply. • Tightening of emission reduction target can lead to less flexible system design. [ABSTRACT FROM AUTHOR]

How dependent are European power systems and economies on natural gas? To answer this pressing question, we coupled a simulation model for assessing security of electricity supply and an economic optimization model. With this, we were able to analyze different reduction scenarios of the amount of gas utilized in the power sector. Our results show that reducing the amount of natural gas in the European power sector by up to 30% has a relatively moderate impact on the security of electricity supply. Restrictions of 40% or more result in substantially higher reductions in electricity demand shortfall and are associated with economic costs of more than EUR 77 billion. Furthermore, we demonstrate that a close coordination of gas distribution on a European level would be instrumental in mitigating negative economic consequences. Finally, it can be deduced that a coordinated delay of planned power plant shutdowns could effectively compensate for reduced gas volumes in the electricity sector. [ABSTRACT FROM AUTHOR]

This paper demonstrates how to consider thermal reserves of overhead lines in optimization problems for congestion management with preventive (pre‐fault) and curative (post‐fault) actions effectively to ensure N‐1 security. Solving congestions curatively allows for higher base loadings and reduced congestion management volumes. At the same time, assets are exposed to higher risks of damage. The two proposed methods incorporate precise permanent and temporary admissible loading constraints for base and contingency situations already at the operational planning stage. The methods ensure that conductor temperatures stay below the assets' thermal limits at all times. The benefits of exploiting thermal reserves are analyzed in a case study to the future German transmission grid of 2030. [ABSTRACT FROM AUTHOR]

Energy System Optimization Models are applied to inform decision making processes and therefore must account for the uncertainty as it exists in the real world. In the recent decade, Modeling to Generate Alternatives gained popularity for considering structural uncertainty in Energy System Optimization Models. Modeling to Generate Alternatives finds numerous near-optimal alternatives, which could give the impression that all alternatives are comparably good. However, if one could compare near-optimal shadow prices of energy demand, certain alternatives would be superior to other solutions. Nevertheless, shadow prices of near-optimal solutions reflect the effort of being different and no approach to calculate expedient shadow prices of near-optimal solutions (comparable to the optimal one) has been presented. A simple approach is suggested and discussed with its implications, using an example scenario. The obtained shadow prices further differentiate the quality of solutions in the near-optimal solution space. Deeper analysis reveals regional or temporal bottlenecks of solutions and can help identify better search directions for alternative solutions. To some extent, the shadow prices highlight effects of parametric uncertainty, even though the proposed method cannot counteract this uncertainty. • Energy System Optimization Modeling benefits from analysis of near-optimal solutions. • Approach to enable expedient comparison of near-optimal shadow prices is presented. • Numerous near-optimal solutions are evaluated using said shadow prices. • Shadow prices differentiate the quality of Modeling to Generate Alternatives' solutions. [ABSTRACT FROM AUTHOR]

Energy system integration enables raising operational synergies by coupling the energy infrastructures for electricity, methane, and hydrogen. However, this coupling reinforces the infrastructure interdependencies, increasing the need for integrated modeling of these infrastructures. To analyze the cost-efficient, sustainable, and secure dispatch of applied, large-scale energy infrastructures, an extensive and non-linear optimization problem needs to be solved. This paper introduces a nested decomposition approach with three stages. The method enables an integrated and full-year consideration of large-scale multi-energy systems in hourly resolution, taking into account physical laws of power flows in electricity and gas transmission systems as boundary conditions. For this purpose, a zooming technique successively reduces the temporal scope while first increasing the spatial and last the technical resolution. A use case proves the applicability of the presented approach to large-scale energy systems. To this end, the model is applied to an integrated European energy system model with a detailed focus on Germany in a challenging transport situation. The use case demonstrates the temporal, regional, and cross-sectoral interdependencies in the dispatch of integrated energy infrastructures and thus the benefits of the introduced approach. [ABSTRACT FROM AUTHOR]

In the field of sector integration, the expansion of district heating (DH) is traditionally discussed with regard to the efficient integration of renewable energy sources (RES) and excess heat. But does DH exclusively benefit from other sectors or does it offer advantages in return? So far, studies have investigated DH only as a closed system or determined intersectoral benefits in a highly aggregated approach. We use and expand an integrated generation and transmission expansion planning model to analyze how the flexibility of DH benefits the energy system and the power transmission grid in particular. First of all, the results confirm former investigations that show DH can be used for efficient RES integration. Total annual system cost can be decreased by expanding DH, due to low investment cost and added flexibility, especially from large-scale heat storage. The high short-term efficiency of heat storage—in combination with electric heating technologies—can be exploited to shift heat demand temporally and, using multiple distributed units, locally to solve electric grid congestion. Although it is unclear whether these results can be replicated in the real world, due to the aggregation and detail of the model, further research in this direction is justified. [ABSTRACT FROM AUTHOR]

Highlights: [•] We develop an energy hub by wind, storage and demand response in distribution network. [•] We present two objective functions for the hub operation under certainty and uncertainty of wind, price and demand. [•] We consider operation costs, emission and reliability in the objective function. [•] We apply two stage stochastic programming of GAMS for solving the hub MILP model under uncertainty. [•] We evaluate effect of DERs and the uncertainties on hub operation costs and reliability in nine cases. [Copyright &y& Elsevier]

Machine-learning diagnostic systems are widely used to detect abnormal conditions in electrical equipment. Training robust and accurate diagnostic systems is challenging because only small databases of abnormal-condition data are available. However, the performance of the diagnostic systems depends on the quantity and quality of the data. The training database can be augmented utilizing data augmentation techniques that generate synthetic data to improve diagnostic performance. However, existing data augmentation techniques are generic methods that do not include additional information in the synthetic data. In this paper, we develop a model-based data augmentation technique integrating computer-implementable electromechanical models. Synthetic normal- and abnormal-condition data are generated with an electromechanical model and a stochastic parameter value sampling method. The model-based data augmentation is showcased to detect an abnormal condition of a distribution transformer. First, the synthetic data are compared with the measurements to verify the synthetic data. Then, ML-based diagnostic systems are created using model-based data augmentation and are compared with state-of-the-art diagnostic systems. It is shown that using the model-based data augmentation results in an improved accuracy compared to state-of-the-art diagnostic systems. This holds especially true when only a small abnormal-condition database is available. [ABSTRACT FROM AUTHOR]

Dynamic thermal rating of overhead lines is a promising approach to increase transmission capacity by calculating weather-dependent thermal ratings (ampacities) of overhead lines in real time instead of using constant ratings. However, knowledge about ampacity is not only needed in real time but also on a day-ahead basis within network operational planning in order to assess network security. As life of humans may be endangered by inadmissible sag of overhead lines when current limits are violated there are high safety requirements concerning thermal ratings. Therefore, ampacity forecasts have to be complemented by a description of forecast uncertainty. So far, there is no method to forecast ampacities on a day-ahead basis considering uncertainty. As a comprehensive description of uncertainty is given by probability densities, this paper presents a novel method to calculate probability density functions of future ampacities based on probabilistic weather forecasts. The method's functionality is proved by application to exemplary data. [ABSTRACT FROM AUTHOR]

• Optimal power and gas flow problem considering power-to-gas. • Quasi-stationary modeling considering DC power flow and gas dynamics. • Scalable approach using successive linear programming. • Use case analyzing dispatch of renewable energy systems. The integrated modeling of power and gas systems gains importance as a result of increasing interdependencies due to bidirectional coupling in renewable energy systems through power-to-gas and gas-fired power plants. The optimal power and gas flow problem (OPGF) aiming to minimize system dispatch costs is mostly applied to small test systems. However, to investigate system-wide effects of sector coupling, large-scale transmission grids must be considered. Due to nonlinearities especially in the pressure loss equation, a nonlinear optimization problem results. This paper aims to demonstrate that successive linear programming, in contrast to other discussed approaches, is suitable for solving large-scale and multi-period OPGF-problems. The presented approach shows high solution quality despite short computing time even for large-scale systems such as the German power and gas transmission grid. [ABSTRACT FROM AUTHOR]

The transition from conventional towards renewable energy systems requires additional transmission capacities and higher operational flexibility to overcome contingency situations. This study presents a novel transmission expansion planning approach for the simultaneous placement of AC systems and power flow controlling technologies including high voltage direct current, phase shifting transformers (PSTs) and thyristor controlled series compensators (TCSCs). The approach is formulated as a mixed‐integer linear programming optimisation problem and the operating point of power flow controlling devices is endogenously determined by minimising expansion costs. Both PSTs and TCSCs are integrated into the optimisation problem by means of new mathematical formulations. PSTs are presented in more detail considering the PST impedance, which is modelled as an equivalent phase shift. The controllable series impedance of TCSCs is also represented as an equivalent phase shift. Exemplary results based on a synthetic 120 bus system show a significant potential of PSTs and TCSCs to reduce expansion costs as well as to lower the requirement for new transmission capacities. The simultaneous employment of these technologies reduces the expansion costs within the test system between 18.7 and 32.4% compared to those costs generated by the sole reinforcement by AC systems. [ABSTRACT FROM AUTHOR]

The energy system decarbonization leads to a decentralization of generation and flexibility. Among the new concepts to integrate distributed flexibility are local energy markets. While a broad range of research investigates local energy markets on a distribution grid level in detail, research on their system impact has been limited. Therefore, we develop a framework to investigate different configurations of local markets as well as the operation of distributed energy resources and their interaction with the wholesale markets. This framework is applied to a pan-European case study with detailed bottom-up modeling of local energy markets in France and Germany. Additionally, transmission grid simulations are carried out to investigate the impact of local trading on grid congestions. Our results show that a direct coordination of distributed flexibility within the wholesale market is more efficient than a preference for local trading. Nonetheless, local energy markets can be used as an incentive for the expansion of distributed flexibility as well as a way to break down the complexity of coordinating millions of distributed assets in a single market. Additionally, our results show that local trading relieves the transmission grid. • Bottom-up modeling of distributed flexibility in France and Germany. • Large-Scale-Modeling of LEMs. • Impact Assessment on Day-ahead market and transmission grid. [ABSTRACT FROM AUTHOR]

• Coupled steady-state and dynamic reactive power planning. • Assessment and planning of voltage control in intra-hour transitions. • Technology-dependent optimisation of active compensation devices to ensure short-term voltage stability. • Mixed-integer linear optimisation considering various voltage control requirements. Planning of reactive power compensation devices as part of the grid planning process is becoming increasingly important due to decreasing reactive power reserves from conventional power plants. Planning such devices requires the consideration of the reactive power demand both during steady-state operation and disturbances as well as gradual power-flow shifts. To control the voltage in these scenarios, a portfolio comprising location, rated power and technology of reactive power compensation devices must be identified. In this paper, a planning approach with a coupled determination of steady-state and dynamic reactive power demand is applied to a generic transmission system. Different characteristic grid use cases are analysed for the identification of the steady-state reactive power demand. The determination of the dynamic demand involves the analysis of critical power-flow shifts within an hourly generation time series. Shifts leading to insufficient voltage stability reserves and high voltage gradients are considered in the planning approach. Furthermore, critical line-outage and short-circuit scenarios are analysed in connection with an increasing demand for dynamic reactive power compensation. Results emphasise that the coupled determination of steady-state and dynamic reactive power demand identifies suitable portfolios of different compensation devices using synergies for voltage control during steady-state operation, disturbances and power-flow shifts. [ABSTRACT FROM AUTHOR]

Integrating increasing shares of weather-dependent renewable energies into energy systems while maintaining high levels of security of supply constitutes a challenge for system operators. The system integration of large shares of variable renewable energy generation requires an effective operation of electricity grids and efficient coordination among grid operators. Hence, the detailed modelling of grid operation has increasingly become important in recent years. Methods for modelling the operation of (extra) high-voltage grids are undergoing persistent enhancements in academia and industry. Existing approaches vary in data granularity and computational methods. Moreover, assumptions on technical details in grid models vary. The results are thus subject to differences in input data and modelling methods. The paper at hand aims to identify the most relevant differences that exist amongst grid simulation models and methods for studying congestion management in a European context. Differences are studied based on a comparison of grid simulation models from eight German energy modelling institutions. The effects of model parameterization and formulation on congestion management results are investigated based on three different case studies focusing on outage simulation, line constraint relaxation and the modelling of cross-border measures. Results indicate that data parametrization can have large impacts on model results with respect to congestion management volumes and the geographic distribution of the respective measures. The analysis also highlights the need to thoroughly calibrate key model parameters. The research findings will assist the grid modelling community and power system planners in simulating congestion management and increase the validity and explorative power of grid simulation models. • Various differences in model formulations for grid operation exist in academia. • Soft-constraints are widely used to detect data inconsistencies and infeasibilities. • Simplified outage simulations particularly impact congestion results in meshed grids. • Parametrization of cross-border measures largely affects congestion volumes. [ABSTRACT FROM AUTHOR]

Abstract: Feeder reconfiguration is one of the most important tasks for loss reduction and reliability improvement in distribution networks. Most of studies so far have investigated reconfiguration problem as a static problem considering fixed level of loads. This assumptions lead to suboptimal solution because of time-varying nature of loads in distribution networks. The switching operation should be cost effective and the reconfiguration scheme should balance the benefits in system loss reduction and reliability improvement against the costs of switching. Moreover, this is a dynamic problem and switching operations of time intervals over a year are not independent. This paper presents a method to determine annual feeder reconfiguration scheme considering switching costs and time-varying variables such as load profiles. In the first stage of the proposed method, to obtain effective configurations, optimal configuration for each day of year is determined independently using harmony search algorithm (HSA) and graph theory. After determination of effective configurations for the network, in the second stage, year is divided into multi equal periods and considering loss cost, interruption cost and also switching cost from a configuration to another configuration, dynamic programming algorithm (DPA) is used to find the optimum annual reconfiguration scheme. The proposed method has been tested on 95-bus distribution network and the obtained results denote that to have an optimum solution it is necessary to compare operation costs dynamically. [Copyright &y& Elsevier]

Electricity prices are the key instrument for coordinating electricity markets. For long-term market analyses, price determination based on fundamental unit commitment simulations is required. Within the European wholesale market, electricity prices result from a market clearing, which finds a welfare-optimal price–quantity tuple considering a coupling of multiple market areas with limited transmission capacity. With increasing exchange capacities in Europe, the precise modeling of the market coupling is required. Many market simulation models use multi-stage approaches with a separation of market coupling and price determination. In this paper, we analyze a new single-stage approach that combines both steps and theoretically and empirically demonstrate its precision by a backtest. For this purpose, we compare a simulated versus a historical electricity price distribution. Moreover, we explain the necessary adjustments for future regulatory developments of the European electricity market regarding flow-based market coupling and propose a concept for the application of future regulatory developments. We demonstrate further developments using a future scenario. [ABSTRACT FROM AUTHOR]

Local flexibility markets (LFMs) are a market-based concept to integrate distributed energy resources into congestion management. However, the activation of flexibility for storage-based flexibility changes the respective state of charge. Compensation in later points of time is needed to regain the original flexibility potential. Therefore, we propose a LFM bid formulation including both flexibility and compensation. Furthermore, flexibility market participation might lead to inc-dec-gaming, i.e., congestion-increasing behavior to maximize profits. However, this inc-dec-gaming might lead to electricity market schedule deviations if LFM offers are not activated. We propose a risk-averse modeling formulation considering the potential non-activation of LFM bids to provide a framework for the assessment of LFM participation comparing different approaches. Our exemplary case studies demonstrate the proposed LFM bid formulation and show the impact of LFM participation modeling on inc-dec-gaming and congestion management costs. [ABSTRACT FROM AUTHOR]

Offshore wind farms are increasingly built in the North Sea and the number of HVDC systems transmitting the wind power to shore increases as well. To connect offshore wind farms to adjacent AC transmission systems, onshore and offshore modular multilevel converters transform the transmitted power from AC to DC and vice versa. Additionally, modern wind farms mainly use wind turbines connected to the offshore point of common coupling via voltage source converters. However, converters and their control systems can cause unwanted interactions, referred to as converter-driven stability problems. The resulting instabilities can be predicted by applying an impedance-based analysis in the frequency domain. Considering that the converter models and system data are often confidential and cannot be exchanged in real systems, this paper proposes an enhanced impedance measurement method suitable for black-box applications to investigate the interactions. A frequency response analysis identifies coupling currents depending on the control system. The currents are subsequently added to the impedance models to achieve higher accuracy. The proposed method is applied to assess an offshore HVDC system's converter-driven stability, using impedance measurements of laboratory converters and a wind turbine converter controller replica. The results show that the onshore modular multilevel converter interacts with AC grids of moderate short-circuit ratios. However, no interactions are identified between the offshore converter and the connected wind farm. [ABSTRACT FROM AUTHOR]

Pathways leading to a carbon neutral future for the German energy system have to deal with the expected phase-out of coal-fired power generation, in addition to the shutdown of nuclear power plants and the rapid ramp-up of photovoltaics and wind power generation. An analysis of the expected impact on electricity market, security of supply, and system stability must consider the European context because of the strong coupling—both from an economic and a system operation point of view—through the cross-border power exchange of Germany with its neighbors. This analysis, complemented by options to improve the existing development plans, is the purpose of this paper. We propose a multilevel energy system modeling, including electricity market, network congestion management, and system stability, to identify challenges for the years 2023 and 2035. Out of the results, we would like to highlight the positive role of innovative combined heat and power (CHP) solutions securing power and heat supply, the importance of a network congestion management utilizing flexibility from sector coupling, and the essential network extension plans. Network congestion and reduced security margins will become the new normal. We conclude that future energy systems require expanded flexibilities in combination with forward planning of operation. [ABSTRACT FROM AUTHOR]

• Integrated optimization of multi-stage expansion planning and grid operation. • Selection of expansion candidates via linear programming relaxations. • Optimizing the grid operation reduces the need for network expansion. • Need for new lines is substituted by the placement of phase shifting transformers. • Minimization of expansion costs by dynamic multi-stage expansion planning. The ongoing transformation of the power system characterized by an increased share of renewable energy sources requires additional transmission capacities. Nevertheless, the need for new transmission capacities can be reduced by optimizing grid operation. This contribution presents a novel approach to the co-optimization of multi-stage transmission expansion planning and grid operation within a mixed-integer linear programming formulation. The expansion via AC systems and phase shifting transformers (PSTs) is combined with the control of PSTs and the determination of congestion management interventions such as redispatch of power plants or curtailment of renewable energies. The number of potential expansion candidates is reduced by linear programming relaxations. Exemplary results based on a synthetic test system containing 120 buses evidence the impact of the proposed approach on overall system costs. The proposed co-optimization reduces the total costs by 16.5 % when applied instead of the sole expansion via AC technology. [ABSTRACT FROM AUTHOR]

Publicly accessible, elaborated grid datasets, i.e., benchmark grids, are well suited to publish and compare methods or study results. Similarly, developing innovative tools and algorithms in the fields of grid planning and grid operation is based on grid datasets. Therefore, a general methodology to generate benchmark datasets and its voltage level dependent implementation is described in this paper. As a result, SimBench, a comprehensive dataset for the low, medium, high and extra-high voltage level, is presented. Besides grids that can be combined across several voltage levels, the dataset offers an added value by providing time series for a whole year as well as future scenarios. In this way, SimBench is applicable for many use cases and simplifies reproducing study results. As proof, different automated algorithms for grid planning are compared to show how to apply SimBench and make use of it as a simulation benchmark. [ABSTRACT FROM AUTHOR]