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Marcus Venzke

Picture of Marcus Venzke
Dr. Marcus Venzke
Room 4.086, building E
Am Schwarzenberg-Campus 3
21073 Hamburg
phone+49 40 42878 - 3378
e-mail

I am in the Institute of Telematics since 1997, having the position of the senior engineer (Oberingenieur) since 2004. Find my private homepage at www.MarcusVenzke.de.

Teaching

Projects

Publications

Kai Hoth, Tom Steffen, Béla Wiegel, Amine Youssfi, Davood Babazadeh, Marcus Venzke, Christian Becker, Kathrin Fischer and Volker Turau. Holistic Simulation Approach for Optimal Operation of Smart Integrated Energy Systems under Consideration of Resilience, Economics and Sustainability. Infrastructures, 6(11), October 2021.
[BibTeX] [Abstract] [DOI] [PDF]
@Article{MDPI_CyEntEE_Simulation_Smart_Energy_System_2021, author = {Kai Hoth and Tom Steffen and Béla Wiegel and Amine Youssfi and Davood Babazadeh and Marcus Venzke and Christian Becker and Kathrin Fischer and Volker Turau}, title = {Holistic Simulation Approach for Optimal Operation of Smart Integrated Energy Systems under Consideration of Resilience, Economics and Sustainability}, pages = , journal = {Infrastructures}, volume = {6}, number = {11}, publisher = {MDPI}, month = oct, year = 2021, }
Abstract: The intermittent energy supply from distributed resources and the coupling of different energy and application sectors play an important role for future energy systems. Novel operational concepts require the use of widespread and reliable Information and Communication Technology (ICT). This paper presents the approach of a research project that focuses on the development of an innovative operational concept for a Smart Integrated Energy System (SIES), which consists of a physical architecture, ICT and energy management strategies. The cellular approach provides the architecture of the physical system in combination with Transactive Control (TC) as the system’s energy management framework. Independent dynamic models for each component, the physical and digital system, operational management and market are suggested and combined in a newly introduced co-simulation platform to create a holistic model of the integrated energy system. To verify the effectiveness of the operational concept, energy system scenarios are derived and evaluation criteria are suggested which can be employed to evaluate the future system operations.
Marcus Venzke, Daniel Klisch, Philipp Kubik, Asad Ali, Jesper Dell Missier and Volker Turau. Artificial Neural Networks for Sensor Data Classification on Small Embedded Systems. Technical Report Report arXiv:2012.08403, arXiv.org e-Print Archive - Computing Research Repository (CoRR), Cornell University, December 2020.
[BibTeX] [Abstract] [URL] [PDF]
@TechReport{Telematik_Venzke_ANNsES, author = {Marcus Venzke and Daniel Klisch and Philipp Kubik and Asad Ali and Jesper Dell Missier and Volker Turau}, title = {Artificial Neural Networks for Sensor Data Classification on Small Embedded Systems}, number = {Report arXiv:2012.08403}, institution = {arXiv.org e-Print Archive - Computing Research Repository (CoRR)}, address = {Cornell University}, month = dec, year = 2020, }
Abstract: In this paper we investigate the usage of machine learning for interpreting measured sensor values in sensor modules. In particular we analyze the potential of artificial neural networks (ANNs) on low-cost microcontrollers with a few kilobytes of memory to semantically enrich data captured by sensors. The focus is on classifying temporal data series with a high level of reliability. Design and implementation of ANNs are analyzed considering Feed Forward Neural Networks (FFNNs) and Recurrent Neural Networks (RNNs). We validate the developed ANNs in a case study of optical hand gesture recognition on an 8-bit microcontroller. The best reliability was found for an FFNN with two layers and 1493 parameters requiring an execution time of 36 ms. We propose a workflow to develop ANNs for embedded devices.
Tobias Lübkert, Marcus Venzke and Volker Turau. Calculating retail prices from demand response target schedules to operate domestic electric water heaters. Energy Informatics, 1(1):31, October 2018.
[BibTeX] [Abstract] [DOI]
@Article{Telematik_EI_2018, author = {Tobias L{\"u}bkert and Marcus Venzke and Volker Turau}, title = {Calculating retail prices from demand response target schedules to operate domestic electric water heaters}, pages = 31, journal = {Energy Informatics}, volume = {1}, number = {1}, day = {10}, month = oct, year = 2018, }
Abstract: The paper proposes a demand response scheme controlling many domestic electric water heaters (DEWHs) with a price function to consume electric power according to a target schedule. It discusses at length the design of an algorithm to calculate the price function from a target schedule. The price function is used by the control of each DEWH to automatically and optimally minimize its local heating costs. It is demonstrated that the resulting total power consumption approximates the target schedule. The algorithm was successfully validated by simulation with a realistic set of 50 DEWHs assuming perfect knowledge of parameters and water consumption. It is shown that the algorithm is also applicable to clusters of large numbers of DEWHs with statistical knowledge only. However, this leads to a slightly higher deviation from the target schedule.

The complete list of publications is available separately.

Supervised Theses

Open Theses

Completed Theses