Gamification of building energy performance with human digital twins

Playing games where people interact and observe their impacts for data-driven modeling of occupant behavior

#11

⛶ Full screen

Aim

This challenge uses an open-source digital twin developed at Empa (https://github.com/Khayatian/nestli) with real-life systems and data. The participants are expected to build on top of the research results, develop ways to incorporate social/occupants' behavior and build the foundation to design a game that would raise public awareness.

Idea

1) data-driven modeling of occupant behavior: In this challenge, we value the modeling of stochastic human behaviors. Given the digitalization of the energy systems, occupants' behavior is taking a more central role in designing automation and control systems. However, occupants are considered (and modeled) passive recipients of the control system to date. To obtain a more realistic assessment of occupants' interaction with building automation and control, this task shall model occupants as active agents that react and occasionally override control decisions, forcing their preferences into the building operation, which the controller has to deal with as disturbance.

2) if time permits, design a game framework based on the digital twin and the developed human twin: Energy end-users are currently taking a passive role in the energy transition. However, they have a much higher impact by changing their behaviors. For example, lowering thermal comfort voluntarily during extremely cold weather would help the energy system to avoid using fossil fuel-based energy production. This awareness may be raised by playing games where people interact and observe their impacts. Our open-source digital twin supports an open-source game for such a purpose. Code is appreciated, but conceptual level development is also sufficient.

Big picture

Building energy demand accounts for a large share of global energy consumption and carbon emission. Advanced building energy management systems can help to reduce energy consumption and carbon footprint. Although the technical design has been much investigated, the impacts of occupant behaviors are rarely considered. In addition, occupants’ behavior can be influenced by great awareness of their impacts and contribution to the energy transition.

See also: https://github.com/khayatian/nestli

Keywords: game design, machine learning, social behavior

🧑🏻‍🏫 EMPA Philipp Heer, Cai Hanmin, Khayatian Fazel Appreciated skills/background: python/game design/data analytics/social science

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