|Aggregator for sending DSM requests based on current power grid state
Meeting the new EU decarbonization targets requires a deep transformation of the power sector. This is why Demand Side Management (DSM) programs are receiving increasing interest as a viable alternative to fossil fuel plants to provide the necessary balancing reserves and optimize grid management. Energy system models are an important tool for assessing the impact of new DSM programmes, but despite their wide use, such models are often criticised for their very optimistic assumptions about residential consumer engagement in demand response and oversimplification of human dimension [1,2].
This project aims to develop an aggregator model for generating DSM requests based on the current state of the power grid to foster usage of flexibility on the consumer side. The model will be integrated into a simulation and used as input for a separated model for simulating the consumer response to the requests.
The project will be developed as follows:
1. The first phase consists of reviewing the literature about DSM strategies.
2. A model has to be designed and implemented, which creates DSM requests based on the available data about the current state of the power grid. For this, the simulation might be split up into two different runs. The first run to collect the state of the grid from simulation. A second run will use the data from the first run and generate and send the DSM requests.
3. The developed model will be integrated in a co-simulation with an activity-based energy demand model, using the Python library demod. This model allows to simulate not only energy consumption but also the daily activities of household members and their expectations of energy services, opening up new possibilities for the socio-technical simulation of flexibility. Additionally, a model for the consumers response to the DSM requests has to be integrated.
4. Several flexibility scenarios will then be simulated and assessed, coupling the developed model with mosaik, a co-simulation framework. An example of a coupling between demod and mosaik is given in .
The candidate will be supervised in joint collaboration between HERUS and OFFIS in order to benefit from the experience of the two laboratories in modelling household energy demand and developing co-simulation scenarios for the energy system, respectively.
. Parrish, Gross, and Heptonstall (2019) “On demand: Can demand response live up to expectations in managing electricity systems?” Energy Research & Social Science, 51, 107-118
. Parrish, Heptonstall, Gross, and Sovacool (2020) “A systematic review of motivations, enablers and barriers for consumer engagement with residential demand response” Energy Policy, 138, 111221
. Barsanti, Schwarz, Constantin, Kasturi, Binder, and Lehnhoff (2021) “Socio-technical modeling of smart energy systems:a co-simulation design for domestic energy demand” Proceedings of the 10th DACH+ Conference on Energy Informatics, 4
|Department of Computing Science
|Type of work
|practical / application-focused
|Type of thesis
|Bachelor's or Master's degree
|Jan Sören Schwarz
familiarity with Python programming language; good knowledge of English.