Jahic, Amra

The importance of electrifying buses in public transportation is increasing massively during the last few years. This owes to the health detrimental emissions of diesel buses and their effect on the climate changes. Correspondingly, the two transportation companies in Hamburg, the Hamburger Hochbahn AG and Verkehrsbetriebe Hamburg-Holstein GmbH (VHH), decided to electrify their bus depots. This ambitious goal is combined with many challenges concerning the design and operation of the charging infrastructure at the minimum costs. Among others also load management, grid impact, power quality. The aim of implementing the presented model is to search for possible usage of flexibility of electric bus depots in the energy market. This is realized by considering the bus depot as an aggregator of positive or negative flexibility. The offering of this flexibility is based on the predefined atypical grid usage in Germany. This enables electricity customers with an annual energy consumption of more than 100,000 kWh to save in grid fees for their load regulation in coordination with grid operators. Nevertheless, the operation of the bus depot has the highest priority in this study to guarantee the ability of buses to travel their routes. This paper analyses three different scenarios for atypical grid usage: the role of load management, the role of a second-life stationary battery and the combination of both cases. As a result, the required supplying periods and capacities of the stationary battery are calculated. Finally, a combined scenario between the supply from the stationary battery and the supply from the grid is presented.

Die fortlaufende Elektrifizierung der Busflotten führt zu neuen Herausforderungen, sowohl für den Flottenbetreiber als auch für das bestehende Energieversorgungssystem. Ein detailliertes Verständnis der Lastprofile der entsprechenden Busbetriebshöfe kann eventuelle Risiken mildern und zusätzlich eine Reihe von unterschiedlichen markt- und netzorientierten Use Cases ermöglichen. Die synthetischen Lastprofile bieten sich hierbei als eine gute Grundlage für die relevanten Design-, Betrieb- oder Optimierungsanalysen. Dieses Paper definiert synthetische Lastprofile der elektrischen Busbetriebshöfe, basierend auf der Analyse der 17 bestehenden Busbetriebshöfe in der Metropolregion Hamburg. Mithilfe einer Clustering-Analyse konnten drei unterschiedliche synthetische Lastprofile definiert werden, abhängig von den Charakteristiken der Busbetriebshöfe und den dazugehörigen Umläufen.

The process of electrification of the public transportation sector is resulting in a growing number of electric buses on the streets. Modelling and simulating the electric bus fleets can not only identify possible issues in time but can also provide valuable inputs for the optimal integration of these buses into existing operational plans and management systems. One of the important requirements for accurate modelling is knowledge of the energy consumption of the buses. This paper uses a data-driven approach to analyze the factors impacting energy consumption. The considered factors are: average daily temperature, trip length, total trip time, state of charge at the beginning of the trip, and average vehicle speed during the trip. Additionally, the impact of different buses and routes is analyzed by considering their ID numbers. The data from 96 different electric buses were collected in the city of Hamburg for 13 months. The analysis of individual parameters provides an insight into the actual operation of electric bus fleets. Additionally, using correlation analysis, it is possible to understand the relationship among all mentioned parameters. The analysis of the energy consumption of electric buses provided in this paper offers valuable inputs for future studies and the successful electrification of further bus fleets.

Designing the infrastructure of bus depots involves numerous factors and considerations, but it is often subject to uncertainties that can affect the efficiency, cost, and overall performance of the depots. This study analyzes various sources of possible uncertainties encountered during the design phase of bus depots and highlights their potential impact. Generally, uncertainties in bus depot infrastructure design can arise from several aspects, including technological advancements and regulatory changes. Also, financial constraints and evolving operational requirements play an important role. The adoption of emerging technologies, such as electric buses, introduces uncertainties regarding the charging infrastructure, energy storage capacity, and compatibility with existing depot layouts. This study considers operational uncertainties, such as changes in the loading of transformers or the occurrence of blackouts, which consequently pose challenges to depot design. This is realized by employing many sensitivity case studies to evaluate various operation and design options under different uncertainty scenarios. The analysis in this study can be used to calculate the loading of transformers at bus depots in advance. Additionally, it is possible to estimate the required stationary battery in the bus depot for supplying the buses during different blackout times.

The electrification of public transportation fleets worldwide can pose a challenge to multiple stakeholders, such as the fleet operator or the operator of the local electrical grid. One of the important prerequisites for the successful integration of these fleets into the existing system is the knowledge of the energy consumption of the buses during their trips. The energy consumption varies depending on multiple factors such as the vehicle or route-related parameters, operational, and environmental parameters. This paper gives an overview of the latest research regarding these influential factors. Another essential prerequisite for the implementation of intelligent management systems for electric bus fleets is the forecasting of energy consumption. Researchers take different approaches to tackle this issue. A review of the latest research considering empirical approaches, physical models, regression, and machine learning is also provided in this paper. The findings of this paper provide a quick overview of different aspects of the energy consumption of electric buses and can therefore support other researchers or decision-makers in their work.

New concepts for the future grid and the energy supply also demand changes in future emergency power supply solutions. It is often not possible to simply replace conventional diesel generators with renewable energy sources. In order to make alternative emergency power supplies viable in the real world, new procedures and structures are needed. A basic distinction is made between stationary and mobile emergency power supplies. Stationary emergency power systems may be found in hospitals, large server farms and other critical infrastructure. The mobile emergency power systems, such as those used by the Technical Relief Agency (THW) or the fire brigade, can be used much more flexibly. One conceptual idea is to use existing electric bus fleet infrastructures as a mobile emergency power supply. This green alternative could replace the conventional diesel generators used today. This paper investigates the use of electric bus fleets as mobile energy storages for emergency power supply usecases. The goal is to examine the general need for buses to be used in a case of emergency power supply, the possible area of coverage depending on the distributed bus depots in Hamburg and the effects on the power requirements of the depots.

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 al-lows 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 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.

High penetration of electric vehicles into the electrical grid requires a grid-friendly management method to decrease possible congestion issues. In this work, a congestion management concept was modeled and simulated. The concept can be implemented by low voltage distribution system operators and charge point operators through a communication protocol. This paper aims to investigate the effectiveness and efficiency of this management method on different penetration scenarios of electric vehicles by using Python and quasi dynamic simulation method in DIgSILENT Power Factory. The modeling of the electric vehicles, as well as other loads and small generators, was conducted with the Monte Carlo simulation and distribution data based on real measurements.

To capture reliable information about the existing flexibility potential of electric vehicles forecasts of charging processes are required in order to allow of utilization and management of available flexibility. Measurements of vehicles from different manufacturers show a heterogeneous behaviour of charging characteristics and charging characteristic switching points when connected to 11 kW charging stations. This paper analyzes the relationship between vehicle-specific easy to identify parameters and the charging characteristics. The proposed generic model is able to capture different charging characteristics with only a small set of parameters, to generate vehicle-specific forecast profiles.