In each MODERATE project newsletter, we’re interviewing one of the project partners to get to know more about them and their role within the project.
This time we’re having an interview with Philipp Mascherbauer, PhD at TU Wien, who is one of our key partners involved in data enhancement and the development of new synthetic datasets describing selected building stock indicators. Philipp will be starting a research stay at CTIC for three months to deepen his knowledge in artificial intelligence and computer science. CTIC is also part of the MODERATE Consortium and is responsible for the MODERATE platform development as well as the storage layer and analytics platform.
During this period, within the MODERATE project, both partners will create together synthetic time series data.
Download the interview in pdf
Interviewer : Thank you for taking the time to speak with us. Could you please provide us with some background on your work at TU Wien and explain yourorganization’s role within the MODERATE project?
Philipp Mascherbauer: I started my PHD almost 3 years ago at TU Wien at the
Energy Economics Group (EEG). Since then I have been working on different
projects mainly related to heating and cooling needs of the building stock.
My core focus was to assess the potential flexibility, the building stock could
provide to the electricity system through the coupling of the heating and the
electricity sector. During modelling residential buildings one of the main
challenges was acquiring reliable building data including building
characteristics as well as consumption profiles.
To tackle this challenge among other things EEG joined in the MODERATE
project. Our main contribution lies within WP4, the data enhancement
methods for the building stock. In modelling building stocks and building
stock data we have a lot of expertise. Through MODERATE we are looking to
broaden our field of expertise by deepening our knowledge in synthetic data
Due to our involvement in numerous projects, which include the creation of
platforms, we bring valuable experience from these previous endeavors to
MODERATE. In WP6 we contribute in identifying user perceptions and user
needs for the platform
I: What inspired you to initiate a research stay abroad at CTIC for this project?
PM: At our institute a research stay abroad is being pushed during the PHD
time. During the project meeting in Gijón I was immediately motivated by the
kind and welcoming people here at CTIC.
Additionally, their field of expertise aligns with my endeavours to deepen my
knowledge in AI and maximize the contribution to WP4.
Therefore, I figured a research stay at CTIC would be a benefit for both, the
project as well as for me personally.
I: Could you explain the significance of creating synthetic time series data within the context of the MODERATE project?
PM: In general, it is very difficult for companies or municipalities (any kind of
entity) to share data which contains personal information as it falls under the
Strictly speaking time series data still contains personal information even if
anonymised as the pattern of the profile could give away personal
information. Synthesizing this kind of data would solve this problem and time
series data could be shared openly.
I: What specific techniques or methods are you planning to employ during your research stay at CTIC for data synthetization in buildings or HVAC identification?
PM: For data synthetisation I am planning to employ Generative Adversarial
Networks or other models depending on what turns out to be most suitable.
I will also use unsupervised learning techniques like regression models and
I: What challenges do you anticipate facing during your research stay, and how do you plan to overcome them?
PM: My main challenge is to create realistic synthetic time series data from
original smart meter data without having any meta data.
To overcome this challenge, we try to cluster the load profiles and then
create synthetic profiles of the respective clusters.
I: What are your plans for disseminating the results of your research?
PM: We plan to present our work at conferences and hopefully publish a paper.
I: How do you think your experience and contributions to the MODERATE project will enhance the collaboration between TU Wien and CTIC in the future?
PM: I hope that we will also collaborate in upcoming international projects.
I: As a marketplace for building datasets and open-source data-driven services, the MODERATE project offers a unique opportunity for innovation in building performance monitoring through data-driven solutions. From TU Wien’s perspective, what do you see as the most important innovation that the project will offer?
PM: From TU Wien perspective the central database for building data on the
MODERATE platform is the most important innovation