PhD position in Heat Transition Built Environment-program

Job description

The research program is focusing on developing new building energy modelling tools to assess the energy performance of buildings with multiple energy carriers, while they also evaluate physical, social and techno-economic characteristics, flexibility aspects such DR actions (implicit and explicit) and interactions with the grid such as charging of EV vehicles.  The program deals also with clustering of the buildings modelling and how these clusters are formulated so that their flexibility and services can be appropriately aggregated and delivered to the grid under different timely contexts such as energy communities, positive energy districts, smart cities etc

So, the two research topics/questions formulated that are fostering the heat transition in buildings are the following:

• How to develop a fully integrated, modular and dynamic bottom-up high-resolution model that can embody key features towards the accurate representation of Grid Interactive Buildings (GIBs).
• How to formulate and model dynamic virtual nodes i.e. cluster of GIBs that can provide exploitable flexibility capacity coming from all carriers (i.e. electricity, heating) to the upstream grid and the operators.

Reseach project description

Do you have a power systems and computer science background and you are eager to combine those two in formulating the building blocks of the future energy system? Then check what research of INBUILT focuses on below:

• INBUILT aims to develop a fully integrated dynamic bottom-up high-resolution model that can embody key features towards the simulation of Grid Interactive Buildings (GIBs). This model builds on the concept of modularity consisting of multiple components, each of which is composed of additional modules, and allowing for more flexibility in terms of possible system configurations and computational efficiency towards a wide range of scenarios to study different aspects of end-use. It will also incorporate future technological breakthroughs and multiple energy carriers in a detailed manner, such as the inclusion of heat pumps or Electric Vehicles and Demand Response actions, in view of energy transitions envisioning the full electrification of the heating and transport sectors.
• Also, the key idea is to develop dynamic clustering based on machine learning techniques to formulate dynamic virtual nodes of GIBs to give momentum and increase further the building-grid integration. Mechanisms on how to aggregate the flexibility of the dynamic clusters shall be investigated. It is important that the modelled flexibility of the cluster can be treated appropriately when matched with the operator needs or the market mechanisms. Of course, by providing flexibility, GIBs participating in the clusters shall be rewarded appropriately and to that end effective disaggregation techniques shall be investigated for efficient rewarding.

Job description

One of the main challenges of this research is the interdisciplinary approach that needs to be fostered for the accurate modeling of GIBs ( e.g. energy, physical characteristics of the buildings and social aspects )and the multi-carrier energy approach that needs to be considered at the end-user side. In order to cope with this challenge, you are going to be steered and mentored by an interdisciplinary team of professors and researchers in both Electrical Engineering and Built environment dpts. It is also expected that you are taking the advised courses for your own growth and development as a researcher.

INBUILT and your research will be a part of the Digital power and Energy Systems lab (EES DigiPES lab) of Electrical Engineering dpt. The lab focuses on intelligent energy network research, including: demand management and flexibility, digital twinning, data analytics, smart grid ICT architectures and systems integration in multi energy systems. The EES group has strong ties with industry both nationally and internationally, with several part-time industry researchers working in the group and a large group of strategic collaboration partners. 

So, you are expected to drive INBUILT research to cover the real-world needs of the actors involved by also considering the societal prism. This means that social characteristics are expected to be considered not only during the modeling of the GIBs but also during the technical application of your outcomes e.g. energy communities application etc.

This position and research project are made possible by the BEHeaT program initiated by the Eindhoven Institute for Renewable Energy Systems (EIRES). EIRES facilitates the collaborative development and swift deployment of new technologies and devices by bringing together TU/e researchers working on materials, systems, and processes for energy storage and conversion. 
EIRES consists of collaborating research groups within TUe. These include over 140 researchers and more than 450 PhDs. EIRES brings these researchers together and creates new network connections between researchers and industry.

Within the focus area of energy transition in the built environment, a large-scale research program was recently launched. This program, BEHeaT, stands for Built Environment Heat Transition. The program is funded with TUe's own resources as well as contributions from industry. The research program has a pragmatic approach.

Within the BEHeaT program, research is conducted into the (further) development of various (new) materials, components and/or systems in relation to intelligent buildings, heat storage, heat networks and/or electricity grids. The focus is not only on physical materials, components and systems, but also on dynamic (predictive) models. We believe that in order to have impact, any research must take systems integration as its starting point. In addition, we believe that technology does not stand alone and should always be seen in relation to the (end) user. In this way, the impact of research results is increased.   

Job requirements

• Motivated researcher, with a background in […power systems and computer science].
• The ideal candidate would have experience with [EnergyPlus, Modelica, Python, Pyomo, Matlab].
• Ability to conduct high quality academic research, reflected in demonstratable outputs.
• A team player who is willing to coach Master's students and working in a dynamic, interdisciplinary team.
• A proven ability to manage complex projects to completion on schedule.
• Excellent (written and verbal) proficiency in English, good communication skills.
• Independent and responsible.
• Can-do mentality

Conditions of employment

A meaningful job in a dynamic and ambitious university, in an interdisciplinary setting and within an international network. You will work on a beautiful, green campus within walking distance of the central train station. In addition, we offer you:

• Full-time employment for four years, with an intermediate evaluation (go/no-go) after nine months. You will spend 10% of your employment on teaching tasks.
• Salary and benefits (such as a pension scheme, paid pregnancy and maternity leave, partially paid parental leave) in accordance with the Collective Labour Agreement for Dutch Universities, scale 27 (min. €2,541 max. €3,247).
• A year-end bonus of 8.3% and annual vacation pay of 8%.
• High-quality training programs and other support to grow into a self-aware, autonomous scientific researcher. At TU/e we challenge you to take charge of your own learning process.
• An excellent technical infrastructure, on-campus children's day care and sports facilities.
• An allowance for commuting, working from home and internet costs.
• A Staff Immigration Team and a tax compensation scheme (the 30% facility) for international candidates.

Information and application

About us

Eindhoven University of Technology is an internationally top-ranking university in the Netherlands that combines scientific curiosity with a hands-on attitude. Our spirit of collaboration translates into an open culture and a top-five position in collaborating with advanced industries. Fundamental knowledge enables us to design solutions for the highly complex problems of today and tomorrow. 

Information

Do you recognize yourself in this profile and would you like to know more?

Please contact prof.dr. J.K. (Koen) Kok, Professor Intelligent Energy Systems, j.k.kok[at]tue.nl.

Visit our website for more information about the application process or the conditions of employment. You can also contact HR Services at HRServices.Flux[at]tue.nl.

Are you inspired and would like to know more about working at TU/e? Please visit our career page.

Application

We invite you to submit a complete application using the apply-button.
The application should include a:

• Cover letter in which you describe your motivation and qualifications for the position.
• Curriculum vitae, including a list of your publications and the contact information of three references.
• List of five self-selected ‘best publications’.

We look forward to receiving your application and will screen it as soon as possible. The vacancy will remain open until the position is filled.