Lichter, J., Hosius, E., Wacker, B., & Schlüter, J. C. (2020). Der Einfluss von Offshore-Windenergie auf die EEX-Strompreise. Zeitschrift für Energiewirtschaft, 44, 85-99. doi:10.1007/s12398-020-00276-8
Simons, J., Wacker, B., Bossert, A., & Schlüter, J. C., Verkehrsökonomische Analyse von Minibustaxiverkehren in der Metropolregion Kapstadt und der Minenstadt Rustenburg in Südafrika, Zeitschrift für Verkehrswissenschaft, 91, 1-27. www.z-f-v.de
Wacker, B., & Schlüter, J. C. (2020). Time-continuous and time-discrete SIR models revisited: theory and applications. Advances in Difference Equations, 2020: 556. doi:10.1186/s13662-020-02995-1
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
Wacker, B., & Schlüter, J. C. (2020). An age- and sex-structured SIR model: Theory and an explicit-implicit numerical solution algorithm. Mathematical Biosciences and Engineering, 17, 5752-5801. doi:10.3934/mbe.2020309
Schlüter, J., Sörensen, L., Bossert, A. et al. Anticipating the impact of COVID19 and comorbidities on the South African healthcare system by agent-based simulations. Sci Rep 11, 7901 (2021). doi.org/10.1038/s41598-021-86580-w
Wacker, B., Schlüter, J. C.(2021). A Cubic Non-Linear Population Growth Model for Single Species: Theory, An Explicit-Implicit Solution Algorithm and Applications. Advances in Difference Equations, 2021: 236. doi:10.1186/s13662-021-03399-5
Kersting, M., Sörensen, L., Bossert, A., Wacker, B., & Schlüter, J. C. (05/2020), Predicting Effectiveness of Countermeasures during the COVID-19 Outbreak in South Africa using Agent-Based Simulation.
submitted@Humanities and Social Science Communications
Herbst, H., Minnich, A., Herminghaus, S., Kneib, T., Wacker, B., & Schlüter, J. C. (03/2020), A Behavioral Economic Perspective on Demand Responsive Transportation, Transportation Research Interdisciplinary Perspectives. submitted@Transportation Research Interdisciplinary Perspectives
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
Wacker, B., Kneib, T., & Schlüter, J. C. (02/2020), Revisiting Maximum Log-Likelihood Parameter Estimation for Two-Parameter Weibull Distributions: Theory and Applications. doi:10.13140/RG.2.2.15909.73444/2
Wacker, B., Schlüter, J. C.. Pipeline for Annual Averaged Wind Power Output Generation Prediction of Wind Turbines Based on Large Wind Speed Data Sets and Power Curve Data submitted@MethodsX
Wacker, B., Schlüter, J. C.. Qualitative Analysis of Two Systems of Non-Linear First-Order Ordinary Differential Equations for Biological Systems submitted@Mathematical Methods in the Applied Sciences
2021 to today University of Applied Sciences Merseburg
2019 to 2020 Next Generation Mobility Group, Department of Dynamics of Complex Fluids, Max Planck Institute for Dynamics und Self-Organization, Göttingen
2017 to 2018 Institute of Mathematics and Image Computing, University of Lübeck, Lübeck
2012 to 2016 Institute of Numerical and Applied Mathematics, Faculty of Mathematics and Computer Science, Georg August University of Göttingen, Göttingen
M.Sc. Georg-August-University of Göttingen
PhD Georg-August-University of Göttingen
3x Supervised and completed Master theses since 2017
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.
Transport Behaviour, Gamification and Nudging
One of the biggest challenges in the mobility transition is human behavior. This is influenced by many different factors and must be considered accordingly for special requirements. This makes it easier to derive more efficient and better economic models and policy implications for these requirements. Our goal here is to enable more sustainable transport behavior. Extrinsic incentives and monetary incentives could be a solution for this, accordingly such concepts have to be identified and tested in experiments.
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.
Demand Responsive Transport Systems in rural Areas
Demographic change is prevalent in rural regions against the backdrop of an aging society as well as out-migration due to a lack of employment opportunities employment opportunities and poor infrastructure. Given a fixed budget for transport operators, declining demand leads to high operating costs per transported customer. This makes the provision of public transport economically inefficient and People in rural areas become highly dependent on private motorized transport. Accordingly, public transport needs to be transformed through digitalization measures. For this purpose, the DRT system Ecobus was developed for rural areas as a door-to-door system.
Research fields involved
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.
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.
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.