My main interest to participate in this team is to exchange ideas about the prediction of hot water demand in residential and non-residential buildings.

nick_efkarpidis

  • 🖍️ Designer
  • ⚙️ Developer
  • 💡 Ideator

As a part of my personal research and sequence of my past collaboration with Aristotle University of Thessaloniki, I work on the development of control strategies for energy management of hybrid systems installed in residential or non-residential buildings. Such buildings consist of RES-based energy carriers, electrical and thermal energy storage systems, as well as heat pumps or other HVAC units. The control strategies can be either rule-based or optimization-based approaches that follow model predictive control (MPC) concepts. Looking on the topic of digital twins, I am triggered by the challenge to predict the hot water demand. I evaluate such control strategies considering various criteria, such as cost, self-sufficiency, self-consumption, battery ageing and thermal discomfort. In the past, I have also developed models that can compute the space heating and space cooling energy demand of buildings.

Contributions

Energy Data Hackdays 2021

September 24 - 25, 2021 Brugg

Dribs