Eindhoven University of Technology (TU/e, https://www.tue.nl/en/) is one of Europe's top technological universities, situated at the heart of a most innovative high-tech region, with a wealth of collaborations with industry and academic institutes. In 2017, TU/e was ranked 15th in Europe in the Times Higher Educational World University ranking for Engineering and Technology. TU/e has around 3,000 employees and 2,300 PhD students (half of which international, representing about 70 nationalities).

Research Programme Description

The envisioned research is part of the research program Intelligent Energy Systems (IES) performed within the Electrical Energy Systems (EES) group of TU/e. Within the IES program, research is conducted into operation and planning of future sustainable energy systems, with an emphasis on electricity systems, markets and systems integration. This research is performed in two research labs: the Digital power and energy systems lab (EES DigiPES lab) and the Electricity markets and power system optimization lab (EES EMPDO lab). The former 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 latter specializes in electricity market design (centralized & decentralized), market products & system services to integrate new technologies, forecasting, market participation strategies and risk management, large-scale, distributed, multi-objective optimization techniques applied to energy markets and power systems and AI for optimization and control in power and 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.

Recently, the Electrical Energy Systems group received grants for nationally-funded projects in Intelligent Electricity Systems. Therefore, this group currently has multiple vacancies in this field. We are currently looking for researchers with strong computer science, modelling & simulation, and research software development skills that want to develop cutting-edge knowledge and software for the energy transition.. The focus of the work will be on the application of intelligent software approaches (distributed control systems, distributed optimization, market mechanisms, multi-scale modelling, etc.), in electrical power systems (energy system flexibility coordination, local energy markets, capacity & congestion management, etc.).

PhD position: Development of Co-simulation tools for decision making in Heat end Electricity Systems of positive energy districts.

The need to address climate change and digitalisation has triggered a revolution in the energy sector by bringing both new challenges and technological solutions. One of the main effects of this revolution has been the growth in the use of Renewable Energy Sources (RES).
Given the volatility of the RES' supply, energy systems are facing a growing demand for flexibility. Among the multiple mechanisms being considered to satisfy that growing demand, one receiving a growing interest is sector coupling. In this mechanism, flexibility is obtained as the result of coupling the different energy networks into one single energy system. Traditionally, evaluation, planning and operations of energy networks was undertaken with limited consideration of what happened in other networks. However, the EU is considering/introducing requirements for the integration of the operations of different energy networks as sector coupling allows for a more efficient use of the energy networks as SOs can use alternative energy networks as sources of flexibility.
To ensure full benefits of sector coupling, the focus of this project will be to identify and quantify the flexibility that can arise from sector coupling. More concretely, this project aims to develop an integrated approach that addresses the challenges posed by future power systems through the coupling of sectors through optimized operation strategies. The main objectives for this PhD plan are defined as follows:

• Investigate the potential of sector coupling scenarios to enhance the flexibility and resilience of future power systems.
• Develop methodologies for integrating sector coupling considerations into energy system operation with a focus on positive energy districts.
• Developing validation tools for the co-simulation of the electricity and heat network for the operational decision-making.
• Investigating scalable models that can be applied to multiple districts and expandable to system level scale.

These goals are achieved through the implementation of a comprehensive analysis on the status of the future energy systems following the steps described below:

• Scenario Analysis: Develop sector coupling scenarios considering the integration of different energy carriers into the electricity network. Different levels of coupling should be foreseen, creating assumptions on the levels of dependencies between the sectors and the carriers.
• Model Development: Build optimization models to analyze the impact of different scenarios on energy system operation. Specifically, decision-making models on siting and sizing of new technologies in the system, with different penetrations percentages based on the coupling scenarios. The network arbitrage in the multi-energy system needs to be modelled.
• Flexibility Analysis: Evaluate the economic viability, environmental sustainability, and technical feasibility of the proposed strategies. This step should give an estimate of the derivable flexibility from the coupled systems using AI-based techniques.
• Tool Development: Develop tools to co-simulate the operation of different energy networks (i.e., electricity and heat) in a district level to ensure the resiliency.

The position is supervised by Dr. N. Neyestani and Prof. dr. J.K. Kok.

We are looking for a highly motivated and pro-active candidate with good communicative skills and English language proficiency. As a PhD candidate you should have the following qualifications

• MSc degree related to modelling and analysis of multi-energy systems, electrical power systems and distributed energy resources.
• Having a good understanding of different energy systems including the flexibility resources and electricity and heat networks.
• Experience in white-box modelling of renewable and distributed energy resources, automated decision making, energy management systems.
• Experience in data-driven modelling, AI techniques, probabilities, stochastic optimization solutions is an advantage.
• Excellent modelling skills and skills in scientific programming and/or numerical computing in languages like Python, Julia, or MATLAB are advantages.
• Enthusiasm in open-source and motivated to learn basic skills of scientific software engineering.
• Ability to work in an interdisciplinary team and interested in expanding the research to real-world application through participating in projects.
• Motivated to develop your teaching skills and coach MSc and BSc students.
• Fluent in spoken and written English (C1 level).
• Dutch language skill is an advantage.

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 P (min. €2,872 max. €3,670).
• 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.