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The interaction between communication technology and the power grids is a major issue in research studies to investigate the effect of cyberattacks, communication failures and other errors to the physical behavior of the power grid. Especially the interconnected digitalized substations of the modern power grids are of interest due to their high-risk potential and dependence of communication technology. Disturbances and negative influences on these key control entities can affect the entire underlying power supply as a critical infrastructure. Recent publications and research projects are trying to investigate the effects by using simulation tools within co-simulation approaches. In this paper, we present a novel approach using a conventional real-time power grid simulation and to combine it with a container-based virtualization of the communication infrastructure. The communication infrastructure contains all the important and necessary components, hosts, devices, and communication aspects to set the network traffic and interactivity of substation automation setups regarding the IEC 61850 standard. This paper will show the feasibility of combining online real-time grid simulation to a container-based virtualization on the process level. The evaluation is done by analyzing occurred time delays and latency about requirements given by IEC 61850 standard. A validation against these transmission time requirements is presented to provide an indication of the feasibility of our approach.

The automated classification of grid disturbances based on phasor measurement units (PMU) is a key application for a fast and reliable monitoring and control of future power systems. The predominant use of dynamic simulations for the training of the classification models can lead to severe misclassifications during the application phase due to measurement induced error signals. As an advancement to standard white noise approaches, an optimization-based error model is introduced for the synthesis of PMU measurement signals with specific noise characteristics. This approach allows a flexible creation of more sophisticated error signals. Extensive simulation studies are performed for a disturbance classification model based on a recurrent neural network using a large electrical transmission grid.

Power Hardware-in-the-Loop (PHiL) becomes more and more an important part at the investigation of dynamics and stability issues of the electrical grids. As derived from Hardware-in-the-Loop (HiL) approach, one of the central PHiL requirements is to feedback measurement signals into the simulation. In PHIL applications, the operational behavior of a connected device is integrated within real-time simulations. With the integration of the Hardware under Test (HuT) into a PHiL test bench, stability issues may arise. Therefore, this paper focuses on the stability investigation and the description of typical PHiL setup and condititions. The frequency domain modelling reveals phenomenon of instability as well as concepts of Interface Algorithm (IA) and Compensation Methods (CM). To investigate the behavior of different devices as HuT, also the HuT is modelled and simulated in the real time environment. In the next step, the analog loopback integrates HuT models into PHiL simulation by using HYPERSIM from OPAL-RT as simulation software (time domain). Analog loopback introduces time delay into the PHiL simulation that would also occur in real PHiL applications with connected devices to build a more realistic environment. The simulation with analog loopback consists of implemented IAs which feedback operational behavior of HuT models into PHiL test bench. In selected simulation approaches, the mentioned technique loops back currents of various loads and inverters. Therefore it is possible to evaluate the feedback of devices with different described methods and their impact on stability and signal fidelity.

In the course of digitalization various technologies which could deeply transform present processes are put forth. As such an innovation, blockchain is attributed to have potential to make energy industry procedures more efficient and to simplify them. The aim of this paper is to examine the applicability of this technology using the change of power supplier as an example. Based on Ethereum a proper blockchain solution for the use-case is developed using smart contracts to handle all processes of the example. Beside qualitative evaluation of manipulation security and privacy, a test scenario is built to measure the speed in which the developed solution allows supplier changes.

Within this survey an approach is presented for the simultaneous online identification and localization of grid disturbances in transmission power systems using different techniques for multivariate time series classification. For the generation of the training data dynamic simulations are performed using DIgSILENT® PowerFactory combined with a Monte Carlo based initial state selection. Within this survey different classifiers are developed and compared with each other including dynamic time warping, support vector machines, shapelets, recurrent neural networks and random forests. The performance is evaluated in terms of classification accuracy and prediction time.

The state of the art in science is to take into account forecast uncertainties in optimization either in the form of variant calculations or in stochastic optimization models. This paper presents an alternative approach for the consideration of forecast uncertainties within model predictive control. The approach defines a guaranteed flexibility range, which is responsible for the compensation of expected forecast errors. It is proven that the risk can be reduced with the help of quantiles based flexibility bands. To implement the approach, a controllable resource is required in the energy system. In this case it is an energy storage device. The result shows that with the help of the new approach it is possible to minimize the forecast uncertainties in the local energy system and thus reduce the impact on the overall system. With this algorithmic approach, the planning reliability in the overall energy system is to be increased.

The scope of this survey is the phasor based event detection under cyber security constraints in modern transmission control centers. A general concept for a physical and cyber event detection is developed as a combination of state-of-the-art disturbance classification and cyber-attack detection methods. This requires the incorporation of heterogeneous data sources and advanced data fusion and analysis techniques. An enhanced and robust recognition of the current grid situation is proposed to distinguish between different scheduled and unscheduled grid events. Furthermore, Digital Twins are considered as new promising technology for control centers and potential benefits for physical and cyber event detection are described.

Within the venture “REGEES” (REGenerative rEnewable Electricity System) a new approach for a Coordinated Market Grid Operation Management (CMGOM) was developed. This approach is investigated in a simulation considering uncertainties. Therefore, the energy time series generator as a method to generate time series for demand and feed-in is described and used to generate simulation input in the form of forecast-scenarios for load and feed-in. Uncertainties in the form of forecast errors and stochastic time series properties are taken into account. The optimization problem, which represents the mathematical description for the acquisition and balancing process of the Balance Responsible Party (BRP), is introduced. Finally, the energy system simulation is described for a test case in order to evaluate the CMGOM approach with consideration of uncertainty. For this purpose, deterministic optimization and two versions of optimization with uncertainties are compared.

More and more active components, i.e. renewable generators, controllable loads, and storages, were integrated to low-voltage distribution grids. They were often interfaced with power electronics and their active participation in the power system may lead to voltage instabilities and power quality problems. Therefore, one research topic was to analyse the dynamic interactions between these active components, and to develop appropriate control architecture and techniques, which are able to avoid the corresponding instabilities and improve the power quality in the low voltage grids. One challenge of such dynamic simulation was to simulate the interacted system with time resolution of millisecond and to ensure the synchronization between them. In this paper, the suitable dynamic models of single-phase power electronic load and three-phase power electronic generator were conducted. These dynamic models were simulated and validated by the voltage-step-response, respectively. The voltage unbalance was used to quantify the interactions between the dynamic models and grid. In the steady state, the power electronic load induced less voltage unbalance comparing to the conventional passive load, because the power electronic load had better power factor. In certain dynamic processes, with the higher penetration of PE components in the LV grid, we observed the significant increase of voltage unbalance, which was induced by the interactions between the controllers of the active components. Such effects should be considered in the design of low-voltage gird system and its components.

The energy transition main targets are increase of energy efficiency and promotion of renewable technologies, hence the number of components with power electronics is growing in the electrical system. The research project VEREDELE examines these effects and resulting interactions in order to identify possible challenges and develop suitable solutions. Especially active components, such as electric vehicles, pose major challenges for the modelling and simulation of these devices. The Power-Hardware-in-the-Loop (PHIL) test bed that built up is a solution to this problem and allows the integration of real devices (loads and feeds) into a grid simulation. A model library developed for system tests, which makes it possible to generate any system states to monitor the real behaviour of the equipment and to conclude on potential critical grid states. Furthermore, the characteristics of the signal source of the simulation system examined in this paper and an evaluation of the usability of the system for the intended investigations is given.

The scope of this survey is the automated extraction of critical events from mixed PMU data sets without prior knowledge about existing failure patterns. An unsupervised procedure is introduced that identifies arbitrary disturbance types (e.g. voltage sags, frequency drops, oscillations) using an ensemble outlier detection approach. For that, different techniques for signal analysis are used to generate features in time and frequency domain. That approach enables the exploration of critical grid dynamics in power systems. Furthermore new failure patterns can be extracted for the creation of training datasets used for online detection algorithms.

The scope of this survey is the compression of PMU data by eliminating redundant information with statistical methods. With that the storage demand in wide area monitoring systems for archiving massive phasor data can be significantly reduced and enables the efficient integration of PMU based applications in modern control centres. Within this paper a general concept is introduced for data reduction in space and time dimension combining different techniques from dimensionality reduction. For this purpose several unsupervised statistical learning methods (e.g. PCA, ICA, NMF) are tested using a real PMU measurement dataset.

Within the venture “REGEES” (REGenerative rEnewable Electricity System) a new approach for a Coordinated Market Grid Operation Management (CMGOM) was developed. It envisages the extension of the balancing process of Balance Responsible Party (BRP) including information of current or estimated grid situation. This paper discusses two different approaches to calculate the restrictions for BRPs by the DSO and the resultant consequences for BRPs optimization. The approaches are applied and assessed in test cases that show their benefits and disadvantages.

An approach for an optimization problem to combine acquisition of a balancing group and grid restrictions given by distribution system operators is introduced in this paper. It is embedded into an extended scheduling system which enables communication between balance responsible parties and system operators. As the optimization problem should be used inside a DayAhead or IntraDay process it was formulated with linear restrictions and with a linear objective function to keep a short computation time. The optimization problem is very modular, hence it can be used for different use cases and is of course easily expandable. We give a proof of concept for the optimization problem and discuss advantages and disadvantages.

The increasing use of fluctuating renewable energy represents a challenge for the German electricity market. Electricity storage plants can provide flexibility to the energy system and the development of new, efficient and economical energy storage technologies is of great importance. In this paper, the use of compressed air energy storage plants in the German electricity market is simulated and a sensitivity analysis is carried out. The optimization of the system is done to minimize at each time step the total system costs. The analysis shows the influence of storage plant parameters such as efficiency, storage capacity and natural gas usage on the dispatch and operation hours. It is performed over one year and for three different future scenarios. The results indicate that utilization of storage plants will increase in each scenario considered from 2025 to 2035 but remains in most cases significantly below the maximum capacity of 3000 h/a power generation. While the operation of storage plants lowers the total electricity cost, earnings per plant and profits are not necessarily positive: the wholesale price signals do not create enough revenues to justify the investment in CAES plants.

An approach for an extended market grid operation is introduced in this paper. Therefore a Market System Operator as a new role in the electricity economy is defined and an extended ENTSO-e scheduling system is developed. Additionally a traffic light system for distribution grids is integrated. The special part of renewable energy sources with their specific character is taken into account. The aim is to retain a sustainable and reliable electricity supply system in Germany while and after the energy transition and to keep a free and liberalized electricity market as per specification from EU commission and German government. The approach helps to extend existing procedures without revising existing role models. This strengthens stakeholders and system operators as well as their communication.

This paper presents the study results of possible plug in electric vehicle (PEV) integration potentials in a commonly occurring rural distribution grid in Germany as a worst case scenario simulation. This worst case consideration means, that all the simulations are running at a fix defined load point at one specific moment in time. After the simulation case definition, like e.g. the so called “strong load case”, the different in Germany commonly occurring PEV-classes are connected step by step to the 0,4 kV grid. So it is possible to compute the maximum integrable amount of PEVs (of each class) in dependency on the grid operation risks. As the core method the conventional Monte Carlo approach were used in a self-implemented characteristic.

The article analyses effects of price signals on the consumption behavior of household electricity customers. It proposes a systematic analysis process consisting of data preprocessing, aggregation steps and clustering methods. This analysis process was applied to two smart meter datasets (Olympic Peninsula Project, RESIDENS). Large fluctuations in customers' response to the same price signal were detected.

By influencing the demand side by means of price signals (Demand Response) additional flexibility potential in electric supply systems can be provided. However, by influencing the demand side typical consumption patterns of previously unaffected consumers are changed. This will lead to increasing uncertainty in load forecasting. This paper deals with the forecast of load time series in consideration of price-based consumption influence. Additional requirements for load forecasting methods resulting from the price elastic consumption behaviour are analysed in this paper. Furthermore, the model residuals of established model approaches will be analysed to explain the disturbance characteristic caused by the price elasticity. Finally, the impact of the model residuals on the load forecast was investigated.

In this paper, a fundamental optimization model containing the German generation and energy storage system has been used to analyze the profitability of pumped-storage power plants within the German energy market. As a result of the optimization, energy prices are calculated based on the power plants' marginal costs according to the merit order principle. This paper demonstrates the influence of increasing model accuracy in the underlying optimization model on the optimization results, particularly regarding the profitability of pumped-storage power plants.

The increasing change of the electrical power system caused by the influence of renewable energy on the power flow in the distribution grid effects mainly the distribution system operators. They have to deal with changed power flow as well as to account for congestions. Therefore they have to take influence on these power flows. One opportunity is represented by variable grid fees which enable a causation-based allocation of grid costs and a higher predictability concerning power system planning. According to the development of pricing in the communication sector flat-rate pricing for grid usage seems to be an appropriate solution. Therefore an approach based on a flat-rate tariff with an additional usage-sensitive component is proposed.

The increasing change of the electrical power system caused by the influence of renewable energy on the power flow in the distribution grid mainly affects the distribution system operators. They have to cope with the changed power flow as well as to account for congestions. Therefore they have to take influence on these power flows. One opportunity is represented by variable grid fees which enable a causation-based allocation of grid costs and a higher predictability concerning power system planning. According to the development of pricing in the communication sector flat-rate pricing for grid usage seems to be an appropriate solution. Therefore an approach based on a flatrate tariff with an additional usage-sensitive component is developed.

In this paper an approach for optimal management of electrical energy storages in distribution grid with high share of renewable energies is presented. Within this approach a multi stage combination of a Storage Scheduling as a long term optimization and a Storage Dispatch as the short term consideration is applied. For this a reference distribution grid with realistic low voltage level structures is applied. The modeling of this reference grid is presented for several levels of the management approach. By means of currently assumed development data for energy generation from renewable fluctuating sources scenarios for the reference distribution grid are developed and the presented approach is investigated in numerical case studies. In conclusion, results of the model calculations are analyzed.

This paper outlines a new approach of distribution system operation utilizing state of the art communication technology. Based on a generalized architecture that is suitable for real time control incorporating fluctuating infeeds from renewables a market driven approach will be outlined. This approach also includes some reference situations related to optimal distribution network power flow with an open and adaptive objective function. The value of the proposed structure will be demonstrated in reference to a first benchmark application within a real distribution network of a public utility.

This paper analyses the application of energy storage systems in distribution networks. Typical use cases are structured with respect to an optimal and integrated design of a energy management system. Based on a proposed architecture typical utilization aspects will be discussed and validated. The main emphasize is given to the adaptation of sophisticated optimization algorithms.