Per Lundqvist

Energy-intense activities and the unpredictable and complex behavior of building occupants lead to an increase in building energy demand. It is, therefore, crucial to study underlying factors for building energy demand related to the users. Higher educational buildings are relevant to study for several reasons: they host the future workforce and citizens, they are predicted to increase in numbers, and they represent a building type less studied. Furthermore, green-rated buildings equipped with smart building systems also represent a research gap that is relevant to address since such a building design involves IoT-functionalities and digital features for the building occupants to interact with. There is also a conceivable risk that if the users know that the building is green-rated and technologically advanced, this may alter their perception of the building operation and thus their behavior. To study the relationship between building occupants and such green and smart educational structure, a survey was conducted in a Swedish higher educational building; as a result, 300 responses were collected and analyzed. The responses revealed that the building occupants act with energy awareness, and they are conscious about energy-saving behaviors. One building feature in particular was studied: the Digital Room Panels (DRPs). The DRP allows the building occupants to modify the indoor temperature and is, therefore, essential for thermal comfort. One key finding from the survey revealed that 70% of the building occupants did not know how the DRPs operate. This study argues that this result can be explained with a lack of communication and user friendliness. Inadequate interactions with building systems could also result in opportunities for energy saving might not be realized. The findings of this case study led to valuable recommendations and suggestions for future research endeavors.

In the light of global climate change and the current energy crisis, it is crucial to target sustainable energy use in all sectors. Buildings still remain one of the most energy-demanding sectors. Campus buildings and higher educational buildings are important to target due to their high and increasing energy demand. This building segment also represents a research gap, as mostly office or domestic buildings have been studied previously. In the quest for thermal comfort, a key stakeholder in building energy demand is the building occupant. It is therefore crucial to promote energy-aware behaviors. The building systems are another key factor to consider. As conventional building systems are replaced with smart building systems, the entire scenario is redrawn for how building occupants interact with the building and its systems. This study argues that behavior is evolving with the smartness of building systems. By means of a semi-systematic literature review, this study presents key findings from peer-reviewed research that deal with building occupant behavior, building systems and energy use in campus buildings. The literature review was an iterative process based on six predefined research questions. Two key results are presented: a graph of reported energy-saving potentials and a conceptual framework to evaluate building occupants impact on building energy use. Furthermore, based on the identified research gaps in the selected literature, areas for future research are proposed.

Today’s commercially-off-the-shelf (COST) wearable devices can unobtrusively capture several important parameters that may be used to measure the indoor comfort of building occupants, including ambient air temperature, relative humidity, skin temperature, perspiration rate, and heart rate. These data could be used not only for improving personal wellbeing, but for adjusting a better indoor environment condition. In this study, we have focused specifically on the sleeping phase. The main purpose of this work was to use the data from wearable devices and smart meters to improve the sleep quality of residents living at KTH Live-in-Lab. The wearable device we used was the OURA ring which specializes in sleep monitoring. In general, the data quality showed good potential for the modelling phase. For the modelling phase, we had to make some choices, such as the programming language and the AI algorithm, that was the best fit for our project. First, it aims to make personal physiological data related studies more transparent. Secondly, the tenants will have a better sleep quality in their everyday life if they have an accurate prediction of the sleeping scores and ability to adjust the built environment. Additionally, using knowledge about end users can help the building owners to design better building systems and services related to the end-user’s wellbeing.

End use energy services have an important role in the ongoing energy transition process by improving the value proposition to the customer through better needs fulfillment and experience and providing system value to the energy system. This study presents a framework for end use energy services, developed as a result of co-creation with multiple stakeholders for a case study in a living lab context. The framework has been co-created using the principles of systems thinking to identify and map both existing and emerging elements and interactions within the energy system and customers. The framework is organized to include aspects from energy system and human system perspectives and divides the energy services development process into three distinct stages. The development stages comprise the strategic planning stage, service design stage, and solution stage. Key considerations are provided for each stage to develop a clearer understanding of the overall end use energy service process.

The purpose of this study is to synthesize the widely used theories about co-creation from two main perspectives: co-creation as an innovation process and co-creation as a design process applied to the service concept design in the built environment context. The architecture, engineering, and construction (AEC) industry do not have much application of end-user-oriented service design in general, especially with intensive co-creation processes. To facilitate such a process, we are using a living lab environment as a laboratorial model of the real built environment, but with the opportunity to have access to the end-users and different types of stakeholders. Using the KTH Live-in-Lab explorative case study, we were able to discuss the concept of co-creation by distinguishing between co-creation as innovation and co-creation as a design process, facilitating the process of co-creation of service concepts for the proposed built environment including methods from both perspectives: innovation and design, and evaluating the process of service concepts co-creation for the built environment from the point of innovation, knowledge transfer, sustainability, and user experience.

Analysis of global energy efficiency of thermal systems is of practical importance for a number of reasons. Cycles and processes used in thermal systems exist in very different configurations, making comparison difficult if specific models are required to analyze specific thermal systems. Thermal systems with small temperature differences between a hot side and a cold side also suffer from difficulties due to heat transfer pinch point effects. Such pinch points are consequences of thermal systems design and must therefore be integrated in the global evaluation. In optimizing thermal systems, detailed entropy generation analysis is suitable to identify performance losses caused by cycle components. In plant analysis, a similar logic applies with the difference that the thermal system is then only a component, often industrially standardized. This article presents how a thermodynamic “black box” method for defining and comparing thermal efficiency of different size and types of heat engines can be extended to also compare heat pumps of different apparent magnitude and type. Impact of a non-linear boundary condition on reversible thermal efficiency is exemplified and a correlation of average real heat engine efficiencies is discussed in the light of linear and non-linear boundary conditions.