The thesis aims at corporate adaptation to climate change impacts in the logistics and transportation industry, especially for the model region Dresden. The paper employs two analyses. The first part deals with a review of the current literature within the topic. 20 references are identified and analysed with a data extraction form. More general adaptation measures are identified in the current literature which can be implemented in the corporate strategy. Crucial effects on company’s operation and its profit have flooding and sea level rise. In comparison adaptation measures, which are identified within five interviews of transportation providers in the model region Dresden, are of technological nature. The interviewed companies adapted significantly to weather extremes in the past. It is identified that heavy precipitation like rain and snow lead to crucial negative impacts to their operations which cause lost profit and customer dissatisfaction in long periods of time. On the other hand these weather conditions may have positive effects in short periods of time. Region-specific analyses in climate change impacts and the implementation of potential adaptation measures for logistics and transportation companies is still in a stage of infancy. Further research is needed on more region-specific analyses and on logistics companies in the model region Dresden as only five of them analysed in this thesis.

The thesis aims at corporate adaptation to climate change impacts in the logistics and transportation industry, especially for the model region Dresden. The paper employs two analyses. The first part deals with a review of the current literature within the topic. 20 references are identified and analysed with a data extraction form. More general adaptation measures are identified in the current literature which can be implemented in the corporate strategy. Crucial effects on company’s operation and its profit have flooding and sea level rise. In comparison adaptation measures, which are identified within five interviews of transportation providers in the model region Dresden, are of technological nature. The interviewed companies adapted significantly to weather extremes in the past. It is identified that heavy precipitation like rain and snow lead to crucial negative impacts to their operations which cause lost profit and customer dissatisfaction in long periods of time. On the other hand these weather conditions may have positive effects in short periods of time. Region-specific analyses in climate change impacts and the implementation of potential adaptation measures for logistics and transportation companies is still in a stage of infancy. Further research is needed on more region-specific analyses and on logistics companies in the model region Dresden as only five of them analysed in this thesis.

Der erste Teil dieser Arbeit beschäftigt sich mit der Frage, welchen Einfluss kurzzeitige Schwankungen der erneuerbaren Energiequellen auf die synchrone Netzfrequenz haben. Zu diesem Zweck wird eine lineare Antworttheorie für stochastische Störungen von dynamischen Systemen auf Netzwerken hergeleitet. Anschließend wird diese Theorie verwendet, um den Einfluss von kurzfristigen Wind- und Sonnenschwankungen auf die Netzdynamik zu analysieren. Hierbei wird gezeigt, dass die Frequenzantwort des Netzes weitestgehend homogen ist, aber die Anfälligkeit für Leistungsschwankungen aufgrund von Leitungsverlusten entlang des Leistungsflusses zunimmt. Der zweite Teil der Arbeit befasst sich mit der Modellierung von netzbildenden Wechselrichterregelungen. Bislang existiert kein universelles Modell zur Beschreibung der kollektiven Dynamik solcher Systeme. Um dies zu erreichen, wird unter Ausnutzung der inhärenten Symmetrie des synchronen Betriebszustandes eine Normalform für netzbildende Akteure abgeleitet. Anschließend wird gezeigt, dass dieses Modell eine gute Annäherung an typische Wechselrichter-Dynamiken bietet, aber auch für eine datengesteuerte Modellierung gut geeignet ist. Der letzte Teil der Arbeit befasst sich mit der Analyse des Risikos von Stromausfällen, welche durch Hurrikans verursacht werden. Hohe Windgeschwindigkeiten verursachen häufig Schäden an der Übertragungsinfrastruktur, welche wiederum zu Überlastungen anderer Komponenten führen und damit eine Kaskade von Ausfällen im gesamten Netz auslösen können. Simulationen solcher Szenarien werden durch die Kombination eines meteorologischen Windmodells sowie eines Modells für kaskadierende Leitungsausfälle durchgeführt. Durch Monte-Carlo-Simulationen in einer synthetischen Nachbildung des texanischen Übertragungsnetzes können einzelne kritische Leitungen identifiziert werden, welche zu großflächigen Stromausfällen führen. / The first part of this thesis addresses the question which impact short-term renewable fluctuations have on the synchronous grid frequency. For this purpose, a linear response theory for stochastic perturbations of networked dynamical systems is derived. This theory is then used to analyze the impact of short-term wind and solar fluctuations on the grid frequency. It is shown that while the network frequency response is mainly homogenous, the susceptibility to power fluctuations is increasing along the power flow due to transmission line losses. The second part of the thesis is concerned with modeling grid-forming inverter controls. So far there exists no universal model for studying the collective dynamics of such systems. By utilizing the inherent symmetry of the synchronous operating state, a normal form for grid-forming actors is derived. It is shown that this model provides a useful approximation of certain inverter control dynamics but is also well-suited for a data-driven modeling approach. The last part of the thesis deals with analyzing the risk of hurricane-induced power outages. High wind speeds often cause damage to transmission infrastructure which can lead to overloads of other components and thereby induce a cascade of failures spreading through the entire grid. Simulations of such scenarios are implemented by combining a meteorological wind field model with a model for cascading line failures. Using Monte Carlo simulations in a synthetic test case resembling the Texas transmission system, it is possible to identify critical lines that trigger large-scale power outages.