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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.

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.

Due to increasing contribution of renewable energy sources to the overall energy production, future control of energy consumption should achieve the principle 'generation following demand'. Within this approach, also known as demand side management, consumers are prompted to alter demands through an incentive signal. This work addresses the use of variable price as such incentive signal to influence power consumption of private households in a controllable manner. The mathematical modelling is based on simulations of optimal power flow and includes several optimisation constraints and criteria, according to which both direct and inverse models are constructed. Therefore, the problem of power signals and price signals is considered as fully-coupled. The analysis is performed for a model, representing typical conditions and scenarios of a residential network with household customers, including solar and wind power plants. The optimisation criteria are constructed with the emphasis on distribution system operators. The results of computations, performed with simplified and extended optimisation models, show a pronounced effect on the overall power consumption, reduction of the extreme values and minimisation of the peaks. Finally, further steps are proposed to extend the model to target various optimisation constraints.

Climate change and limited availability of fossil fuel reserves stress both the importance of deploying renewable energy sources (RES) for electricity generation and the need for a stronger integration of regional electricity markets. This analysis focuses on North African (NA) countries, which possess vast resources of renewable energy but whose electricity supply is still largely dependent on fossil fuels. An analysis of cost-optimized deployment scenarios for RES is conducted in five NA countries in 2030 and 2050. Three electricity models are combined to derive results covering trans-regional to sub-national level, including a detailed analysis of grid capacities and future transmission challenges. Further, opportunities for integration of European and NA electricity markets are evaluated. Results confirm that, by 2050, high RES shares - close to 100% - are possible in NA. Wind energy is the dominant technology. Concentrated Solar Power (CSP) plants also play an important role with rising RES shares due to the possibility to store thermal energy. Electricity exports to Europe gain particular importance in the period after 2030. Substantial transmission grid reinforcements on AC-level and the construction of a high voltage DC overlay grid are prerequisites for the forecasted scenarios.

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.

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.

Growing shortage of fossil resources and an increasing demand of individual mobility worldwide require technology alternatives to existing mobility solutions. Electric vehicles (EVs) as one possible solution have moved into the focus of research and development. To maximize the positive environmental effect of EVs, it is proposed to charge them with respect to the availability of renewable energies. As the number of EVs will grow in the near future, their impact on the power distribution grid is no longer neglectable. Related research shows that unmanaged charging of EVs could result in overload situations or voltage instabilities. To overcome this, methods are proposed to manage the charging process holistically. Herein EVs become substantial elements of intelligent power grids (Smart Grids). As of today, research in the area of Smart Grids focuses mainly on either energy aspects or communication aspects while neglecting the interoperability of energy and communication related aspects. In this paper, an insight into Information and Communication Technology (ICT) aspects with respect to Managed Charging of EVs in Smart Grid environments will be given. Based on the use case of Managed Charging, requirements will be analyzed, results will be derived, and ICT solutions will be proposed with a set of recommendations for Smart Grid architectures.

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.

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.

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.

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.

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 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.