print page

Tobias Lübkert

Picture of Tobias Lübkert
Tobias Lübkert
Room 4.075, building E
Am Schwarzenberg-Campus 3
21073 Hamburg
phone+49 40 42878 - 3704
fax+49 40 427 - 3 - 10456
e-mail

I received my Master's degree in Computer Science and Engineering at Hamburg University of Technology in July 2015. Since November 2015 I am working as a research assistant at the Institute of Telematics.

Teaching

Projects

Publications

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.
@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.
Tobias Lübkert, Marcus Venzke, Nhat-Vinh Vo and Volker Turau. Understanding Price Functions to Control Domestic Electric Water Heaters for Demand Response. Computer Science - Research and Development, 81–92, February 2018.
@Article{Telematik_Demand_Response_DEWH_2017, author = {Tobias L{\"u}bkert and Marcus Venzke and Nhat-Vinh Vo and Volker Turau}, title = {Understanding Price Functions to Control Domestic Electric Water Heaters for Demand Response}, pages = {81-92}, journal = {Computer Science - Research and Development}, volume = {}, month = feb, year = 2018, }
Abstract: A well-known mechanism for demand response is sending price signals to customers a day ahead. Customers then postpone or advance their usage of electricity to minimize cost. Setting up price functions that adapt the customers' load to availability is a big challenge. This paper investigates the feasibility of finding day-ahead price functions to induce a desired load profile of Domestic Electric Water Heaters (DEWHs) minimizing their electricity cost for demand response. Bilevel optimization is applied for a single DEWH using a simplified linear model and full knowledge. This leads to a solvable bilevel problem and allows understanding optimality of price functions and resulting heating profiles. It is shown that with the resulting price functions the DEWH may select many significantly different heating profiles leading to the same cost. Thus the price does not uniquely induce the desired heating profile. The acquired knowledge forms the basis for a procedure to create price functions for controlling the load profile of many DEWHs.
Tobias Lübkert, Marcus Venzke and Volker Turau. Appliance Commitment for Household Load Scheduling Algorithm: A Critical Review. In 2017 IEEE International Conference on Smart Grid Communications (SmartGridComm), October 2017, pp. 527–532. Dresden, Germany.
@InProceedings{Telematik_SGC_2017, author = {Tobias L{\"u}bkert and Marcus Venzke and Volker Turau}, title = {Appliance Commitment for Household Load Scheduling Algorithm: A Critical Review}, booktitle = {2017 IEEE International Conference on Smart Grid Communications (SmartGridComm)}, pages = {527-532}, day = {23-26}, month = oct, year = 2017, location = {Dresden, Germany}, }
Abstract: The paper analyzes the behavior of two demand response algorithms, both claiming to minimize the energy cost regarding time-varying prices in an optimal way by iteratively scheduling heating phases of water heaters considering hot water consumption. Four issues of the well known algorithm by Du and Lu are identified, which lead to suboptimal behavior. Proposed enhancements lead to an algorithm similar to the second, recently published, method of Shah et al. The effect of each enhancement and its combinations are analysed simulatively reducing the costs.

The complete list of publications is available separately.

Supervised Theses

Completed Theses