The reduction of greenhouse gas and pollutant emissions is a major issue in modern society. Therefore, environmentally friendly technologies like fuel cells should replace conventional energy generation plants. Today, fuel cells are used in households for CHP (combined heat and power) applications, for emergency power supply in many stationary applications and for the power supply of cars, buses and ships and emergency power supply of aircrafts. A significant challenge is the optimal electrical grid integration and selection of the appropriate grid protection mechanism for fuel cell applications. For this, the short circuit capability and behavior needs to be known. This paper gives a mathematical estimation of the short circuit behavior of fuel cells. Five main transient and dynamic phenomena are investigated. The impact of the main transient effect for the provision of additional short circuit energy is simulated, and the simulation is experimentally validated. For this purpose, a 25 $\mathrm{c}$ $\mathrm{m}$ ${}^2$ single cell consisting of a Nafion^TM 212 membrane and carbon cloth electrodes with a catalyst loading of $0.5$ $\mathrm{m}$ $\mathrm{g}$ / $\mathrm{c}$ $\mathrm{m}$ ${}^2$ Pt is analyzed. The magnitude of the transient short circuit current depends on the operating point right before the short circuit occurs, whereas the stationary short circuit current of fuel cells is invariably about twice the operational current. Based on these results, a novel fuel cell model for the estimation of the short circuit behavior is proposed.

One of the crucial steps for a successful integration of electric bus fleets into the existing electric power systems is the active and intelligent usage of their flexibility. This is important not only for reducing the eventual negative effects on the power grid but also for reducing energy and infrastructure costs. The first step in the optimal usage of flexibility is its quantification, which allows the maximum provision of flexibility without any negative effects for the fleet operation. This paper explores the available flexibility of large-scale electric bus fleets with a concept of centralized and unidirectional depot charging. An assessment of available positive and negative flexibility was conducted based on the data from two real bus depots in the city of Hamburg, Germany. The analysis shows the biggest flexibility potential was in the period from 16:00 h to 24:00 h, and the smallest one was in the periods from 08:00 h to 16:00 h, as well as from 02:00 h to 08:00 h. The paper also gives an overview of the possible markets for flexibility commercialization in Germany, which can provide an additional economic benefit for the fleet operators. A further analysis of the impact of parameters such as the timeline (working day or weekend), charging concept, ambient temperature, and electrical preconditioning provides an additional understanding of available flexibility.

The encoding of high-resolution energy profile datasets from end-users generated by smart electricity meters while maintaining the fidelity of relevant information seems to be one of the backbones of smart electrical markets. In the end-user sphere of smart grids, specific load curves of households can easily be utilized to aggregate detailed information about customer’s daily activities, which would be attractive for cyber attacks. Based on a dataset measured by a smart meter installed in a German household, this paper integrates two complementary approaches to encrypt load profile datasets. On the one hand, the paper explains an integration of a lossy compression and classification technique, which is usable for individual energy consumption profiles of households. On the other hand, a perturbation approach with the Gaussian distribution is used to enhance the safety of a large amount of privacy profiles. By this complete workflow, involving the compression and perturbation, the developed framework sufficiently cut off the chance of de-noising attacks on private data and implement an additional, easy-to-handle layer of data security.

The high importance of demand-side management for the stability of future smart grids came into focus years ago and is today undisputed among a wide spectrum of energy market participants, and within the research community. The increasing development of communication infrastructure, in tandem with the rising transparency of power grids, supports the efforts for deploying demand-side management applications. While it is then accepted that demand-side management will yield positive contributions, it remains challenging to identify, communicate, and access available flexibility to the flexibility managers. The knowledge about the system potential is essential to determine impacts of control and adjustment signals, and employ temporarily required demand-side flexibility to ensure power grid stability. The aim of this article is to introduce a methodology to determine and communicate local flexibility potential of end-user energy systems to flexibility managers for short-term access. The presented approach achieves a reliable calculation of flexibility, a standardized data aggregation, and a secure communication. With integration into an existing system architecture, the general applicability is outlined with a use case scenario for one end-user energy system. The approach yields a transparent short-term flexibility potential within the flexibility operator system.

Owing to the immense climate changes in recent years, the city of Hamburg has decided to allow the purchase of only emission-free buses for public transportation. Meanwhile, Hamburg focuses on the implementation of electric buses. For this purpose, the two public transportation companies in Hamburg which are the Hamburger Hochbahn AG (HOCHBAHN), and the Verkehrsbetriebe Hamburg-Holstein GmbH (VHH) decided to build new charging infrastructure for electric bus depots. In addition, they started by electrifying their existing stations. This study proposes an optimal method for electrifying bus depots by modularizing the subsystems in electrical power systems. An approach that allows the study of different configurations of power system components. Analyzing these configurations results in the conclusion of the most technically feasible configuration achieving the lowest cost. Furthermore, the model objectives include reducing the required area, which is a challenging criterion for bus depots in many cities. Mixed-Integer Quadratic Programming (MIQP) is used to generate this combination based on predefined constraints that must satisfy all implemented constraints of the system.

The increasing number of decentralized power generators in the low-voltage and medium-voltage grid induce multiple short-time power- balanced areas. These areas intensify the problem to determine the dynamic energy flow of the distribution grid. The identification of power- balanced grid parts is a time consuming and computationally intensive process. Hence, this contribution presents a simplified identification method that has minor computational effort. The method computes a simplified energy flow over more than one voltage level. So, it is even possible to identify power- balanced grid parts that are spread over different voltage levels. For evaluation and validation the method is compared to a traditional grid simulation with DIgSILENT PowerFactory.