PhD position (B2E Lab): Dynamic tariffs, intelligent control and smart consumer interaction for the low-voltage grid of the future

In der aktuellen Covid-19 Situation laufen die Rekrutierungen weiter. Es kann dabei allerdings zu Verzögerungen kommen. Vielen Dank für Ihr Verständnis.

100%, Zurich, fixed-term

The Bits to Energy Lab is dedicated to developing information systems that promote behavior change. Our research includes machine learning to identify behavioral characteristics, theories to explain and predict consumer behavior, and behavioral interventions that lead to desired motivation and support users in their daily decisions. We strive to validate our findings in real-world applications, using IT simultaneously as a research tool and a means to implement our findings.

Project background

Decentralized power generation and increasing electrification in the areas of mobility and heating are placing considerable demands on the power grid. Variable loads and local electricity storage can help relieve the load on the grid and thus enable the further expansion of local generation. In order to achieve this, however, a high self-consumption rate must not be rewarded as in the previous system, but rather a high level of grid efficiency. The goal of the project is to enable the low-voltage grid of the future with increased penetration of renewable energy by providing a high grid efficiency and fair cost distribution. The approach aims to steer the customer behavior via dynamic tariffs, which influence the grid load, increase the attractiveness of intelligent control mechanisms and finally promote a socially desirable behavior of the grid participants.

Job description

Central to the implementation of the objective is the understanding of the interplay between tariff setting and customer reactivity. For this purpose, market mechanisms as well as static and dynamic tariff models are defined. The basis for modeling and implementation are tools based on optimization and learning algorithms (artificial intelligence) for automated energy management. By optimizing and automating the interactions, the foundation is laid for reliable and cost-efficient grid operation. The results will provide important data and insights for the Swiss electricity system of the future and the future design of the regulatory framework.

At the Bits to Energy Lab, you will focus on market mechanisms and tariff design, user behavior modeling and empirical analysis, and user interaction and impact analysis. You will also contribute to the work of our project partners from ETH's Power Systems Laboratory by helping to develop and analyze smart grid control mechanisms, and from our partner utility company by accompanying the project's field tests.  

The 3- to 4-year PhD position is based in the Professorship of Information Management at ETH Zurich, Switzerland. There will be a requirement to take courses at ETH Zurich as part of the PhD training programme.

Your profile

The following attributes, qualifications, and experience would be highly advantageous:

• MSc degree in computer science, electrical engineering, or industrial engineering, or in psychology, economics, or statistics with additional courses in engineering or machine learning
• Experience with or strong interest in statistical modeling, empirical analysis, power grids, surveys, and consumer behavior.
• Ability to work in a team and good communication skills
• Ability to structure your work and interest in collaborating with industry partners
• Excellent knowledge of written and spoken German
• Excellent command of written and spoken English

ETH Zurich

ETH Zurich is one of the world’s leading universities specialising in science and technology. We are renowned for our excellent education, cutting-edge fundamental research and direct transfer of new knowledge into society. Over 30,000 people from more than 120 countries find our university to be a place that promotes independent thinking and an environment that inspires excellence. Located in the heart of Europe, yet forging connections all over the world, we work together to develop solutions for the global challenges of today and tomorrow.

Working, teaching and research at ETH Zurich