GameOpSys - Gamification for optimizing the energy consumption of buildings and higher-level systems

The central goal is the development of a mobile application that enables the energy optimization and planning of buildings, neighborhoods and higher-level energy systems through the participation of the user and the user as a new source of data and information. The development of the application is strongly transdisciplinary and integrates mathematical methods of simulation and optimization as well as psychological aspects of user behavior in order to develop new business models and open up new markets.

Short Description

Starting point / motivation

A central challenge for future energy systems is to coordinate the available energy with local, temporal and quantitative demand. This transition to sustainable systems is putting increasing pressure on politicians, urban planners, energy suppliers and network operators. The user's participation as well as the utilization of new data and information sources still shows a great potential for energy optimization and planning of buildings, quarters and superordinate energy systems.

Contents and goals

The central goal of the project GameOpSys is the development of a mobile application which generates usable data and information for the user's own cost and energy optimization (electricity and heat) by participation via gamification. The combination of this data with Smart Home applications and the Internet of Things enables the overall goal of cross-sectoral energy optimization and improved planning of buildings, neighborhoods and higher-level energy systems.


The transdisciplinary approach of the project has the following innovative content compared to existing concepts and services:

The potential of user participation through gamification as well as the utilization of data and information is significantly increased by integrating mathematical and computational methods into the mobile application.

While relevant technologies and developments are based on simplified models (e. g. economic time series analyses), the integration of detailed physical and data-driven models (machine learning) in combination with sophisticated optimization methods has significant advantages: Energy consumption, costs or emissions can be minimized based on the solution of a dynamic optimization problem for the next few hours and days. Dynamic effects and inertia such as component activation for heating and cooling can be taken into account.

The user can - optionally in connection with smart home applications - define setpoints for room temperatures or periods of use for household appliances, for example. The energy supplier has the possibility to influence the process of optimization through incentives and reward systems.

Social-psychological findings of user behaviour are an integral part of the development and innovative market concepts (blockchain etc.) are taken into account.

Expected results

The application is implemented for maximum flexibility in terms of its commercial development (app-ready, based on rapid prototyping methods). A fundamental evaluation of the development platform and architecture is also carried out in order to guarantee maximum flexibility for the planned further development (commercial development after the end of the project).

Project Partners

Project management

dwh GmbH

Project or cooperation partners

  • Karl-Franzens-Universit√§t Graz / Institute of Psychology
  • TU Graz / Institute of Software Technology
  • TU Wien / Institute of Energy Systems and Electrical Drives Energy Economics Group

Contact Address

dwh GmbH
Neustiftgasse 57 - 59
A-1070 Wien
Tel.: +43 (1) 526 55 26