Kern, L., Seebaß, J. V., & Schlüter, J. C. (2019). Das Potenzial von vertikalen Windenergieanlagen im Kontext wachsender Flächennutzungskonflikte und Akzeptanzprobleme der Windenergie. Zeitschrift für Energiewirtschaft, 43, 289-302. doi:10.1007/s12398-019-00264-7
Wacker, B., Seebaß, J. V., & Schlüter, J. C. (2020). A modular framework for estimating annual averaged power output generation of wind turbines. Energy Conversion and Management, 221: 113149. doi:10.1016/j.enconman.2020.113149
Hosius, E., J., Seebass, J., V., Wacker, B., Schlüter, J. C.. The Impact of Offshore and Onshore wind Energy on European Wholesale Electricity Prices submitted@Energy Economics
v. Detten, J., Seebass, J., V., Schlüter, J. C., Hackelberg, F.. Influence of Onshore Wind Turbines on Land Values
Books & Technical Reports
Technical Report 6 "Energy Trade"
Technical Report: Machbarkeitstudie zur Ansiedlung von Hochtechnologien in Schleswig-Holstein.
Projects / Transfers Involved
The most important energy source from the field of renewable energies in europe is wind. Currently, wind can still be interpreted as a stochastic variable. Accordingly, we try to improve our understanding of the structure of the wind with mathematical and statistical tools.
Wind energy represents an important future economic sector due to the increasing interest in renewable energy worldwide. For this reason, wind turbine performance prediction is an important task for economists. Accordingly, the field of energy economics is in a state of flux and offers a variety of new research questions.
Wind energy is gaining an ever-increasing share in the electricity mix of many countries. Our goal is to estimate the wholesale price and thus provide planning certainty in the markets and reduce the impact of fluctuation of wind energy. For this analysis, we treat offshore and onshore wind energy as variables to be considered and their impact on the European Energy Exchange. Using these models, we can identify various parameters and how they affect wholesale electricity prices.
Transport in Metropolitan Areas
Transportation in the megacities of the has a multitude of problems. One of the biggest core problems is the inadequate public transportation system which leads to a multitude of other problems such as extreme traffic congestion, long commute times, air pollution, fatal traffic accidents. The external cost of these consequences is a high damage to the economic development of these cities. With the continuous growth of these cities, this research area is continuously gaining importance to provide for a more sustainable world.
Agent Based Simulations and Policy Recommendations for Epidemics in South Africa
The People´s Republic of China was the first region to be affected by a global pandemic outbreak in January 2020. COVID-19 spread very quickly around the globe, presenting the international community with new dimensions of economic, social and moral problems. Countries responded by making macroscopic decisions for their nations. The individual regions were not equipped with the appropriate applications to be able to act regionally. Accordingly, micro-management decision support tools could be developed by us to advise the regional decision makers.
Socio-Economic Optimisation of Public Transport Systems in Africa
While urbanization and population growth are expanding city boundaries, public transportation systems are required to accompany this process in order to provide accessible public transport. The results of this study provide a basis for further analyses of public transport systems around the world to determine deficiencies in parameters and service design. It also contributes to the toolkits for the assessment of public transport services within a city and provides guidelines for political processes.
AI for Aerospace Technology
A major driver of climate change is flying, so we are striving to make this more sustainable. in doing so, we are focusing on researching the effects of operating conditions on aircraft engines to improve the timely planning of maintenance events and optimize them. To do this, we use machine learning mainly with time series of aircraft engines and numerical weather prediction models. The research aims to improve fuel efficiency and increase component longevity. This should enable plant operators and service providers to reduce costs and environmental footprint.
In a comparison of the German states, Schleswig-Holstein scores below average on indicators such as gross domestic product per employee and research and development spending. One possible remedy against such scenarios is to provide impetus for technological innovations that have an impact on both economic growth and industrial development.
Transfer Project 2:
Status: Before Take Off
Research fields involved
Applied Artificial Intelligence
Due to the large amount of data from the areas of transportation and energy, we use artificial intelligence to analyze it. New use cases for artificial intelligence are emerging in the process.
Wind energy is the backbone of renewable energies in Europe. The high fluctuation of this energy source is one of the main problems to be solved. Accordingly, complementary technologies and smart power grids are promising approaches.
Renewable energies lead to strong fluctuations on the markets. accordingly, these have to be analyzed and understood more precisely in order to supply the economy with energy and to maintain its functionality.
The combination of methods from the transport sector and the inclusion of digital technologies enable new applications in the field of public health. In this context, it is possible to take a look at the micro level and to model regions in a targeted manner.