ETHOS Student Projects

This project is offered in collaboration with the Urban Energy Systems group at EMPA.

The proposed project will develop a common database of metering and sub-metering data from Swiss households. This data will be used to develop non-intrusive load monitoring (NILM) algorithms and customer segmentation models. The project will also evaluate the demand flexibility potential of Swiss households and develop targeted demand flexibility programs. The project will develop new tools and knowledge that can be used to design and implement effective demand flexibility programs in Switzerland. The project will also contribute to the development of a more reliable and sustainable power system.

The key steps envisioned for the completion of the project are as follows:

• Literature review
• Data collection and preparation
• NILM algorithm development and validation
• Customer segmentation modeling
• Development of household energy model
• Demand flexibility analysis
• Documentation

Supervisor: Andrew Sonta ([email protected])

Building energy demand flexibility helps with balancing the grid and increasing uptake of local renewable generations. In office buildings, the majority of the energy consumption, such as HVAC, lighting, and plug loads, are usually dominated by occupants’ behavior. Thus, the recent trend of hybrid working and other types of flexible work arrangement (FWA) might unlock much further energy flexibility potential. However, how FWA actions influence the building occupancy level and therefore the consequent energy consumption are very case-specific and remains unclear in general. In this project, students will conduct simulation study on a joint-energy-occupancy simulation testbed to discover these underlying relationships, and will also be involved in development of meta-models for fast evaluation of the impacts from FWA on energy energy flexibility.

Supervisor: Yufei Zhang ([email protected])

The importance of the design of the built environment on human behavior and experiences has been studied, but largely from a theoretical perspective and lacking empirical evidence. This project aims to understand where data-driven analysis is needed and to conduct data analysis to better characterize the human and built environment relationships. Some components of this topic include investigating how physical features of the existing built environment influence human outcomes and experiences (e.g., social cohesion and well-being) and how human behaviors are interacting with the built environment (e.g. active mobility such as walking). The detailed focus of this project will be shaped based on students’ interests and background. 

Supervisor: Kanaha Shoji ([email protected])

In most industrialized nations, the building sector accounts for about 40% of the total energy consumption. A significant share of this energy is used to thermal control buildings and provide thermally comfortable indoor environments. However, technical building systems are typically designed and operated considering fixed set-point temperatures based on the ‘one-size-fits-all’ principle assuming universal thermal comfort requirements. Furthermore, the indoor environment frequently changes abruptly across buildings or between various parts within a single building, and the steady-state temperature settings are the exception rather than the rule. Building temperature ranges should instead be based on real-time empirical evidence regarding the needs of its occupants. This project will develop a new modeling strategy that considers the occupant and his/her needs, linking perception to an action (behavior). Moreover, this project will also investigate the application of ‘personalized environmental control systems’ (PECS) as a means to improve personal thermal comfort while potentially reducing energy consumption.

Supervisor: Matteo Favero ([email protected])