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 a model for simulating consumer response to explicit DSM requests, based on socio-technical aspects. This study will target devices that are pilotable by the occupants and represent an interesting flexibility potential, such wet appliances (i.e., dishwasher, washing machine, and tumble dryer) or heating system (i.e., heat pump) and electric vehicles. The project will be developed as follows:

1.    The first phase consists of reviewing the literature about DSM strategies, methods for modelling consumer response and collecting empirical findings from trials and pilot projects.

2.    The empirical data found will be supplemented with reasonable assumptions in order to develop a simplified model for simulating consumer response to explicit DSM requests. The aim is to develop a model capable of considering factors other than the economic incentive, such as electricity emission intensity, contribution in grid stability, domestic comfort and consumer daily routines/needs.

3.    Model design and implementation will be based on 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.

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 [3].

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.

Methods: probability and statistics methods; numerical analysis and simulation; Python programming language; optimisation methods.

Starting date: Spring 2022

References

[1]. 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

[2]. 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

[3]. 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

Knowledge of fundamentals of probability, statistical and numerical analysis; familiarity with Python programming language; good knowledge of English.