苏黎世联邦理工

Assessment and optimization of a fully-renewable European energy infrastructure

项目介绍

The Risk and Reliability Engineering (RRE) group, within the Institute of Energy and Process Engineering at ETH Zurich, is looking for a doctoral student working on the assessment and optimization of a future fully-renewable European energy infrastructure. The PhD position is well connected with other research projects at RRE, which deal with the assessment and optimization of a variety of energy systems and energy-carrier networks, as well as with the assessment of policy mechanisms to foster the transition to fully-renewable energy systems. The RRE group is headed by Prof. Dr. Giovanni Sansavini and generally focuses on the optimization and assessment of complex systems and infrastructures with an emphasis on safe and resilient design and operations.

Project background

The transition to a net-zero-carbon-emissions (net-zero) European energy system requires a significant increase in renewable generation capacity with respect to current values. However, where exactly all this infrastructure should be built, how it should be fostered, and how it will interact with different energy and industry sectors, is still controversial. This calls for a holistic analysis of future energy systems within the energy trilemma paradigm, where economic, environmental, and security performance must be balanced.

Job description

The goal of the project is to develop decision-making tools for supporting investment and operation decisions addressing the questions above. This will be done:

  • by adopting state-of-the-art modeling techniques to simulate the future spatial and temporal evolutions of a fully-renewable electricity system, alongside their impact on electricity prices and carbon intensities of the electricity grids;
  • by expanding and developing cutting-edge optimization models to determine the optimal system evolution when looking at economic, environmental and security indicators;
  • by assessing the impact of state-of-the-art market mechanisms, such as power purchase agreements (PPAs), on the deployment of renewable energy sources;
  • by investigating the coupling of the electricity system with a variety of energy sectors where electricity demand will most likely increase in the future, such as heating and mobility.

To address these points, you will have access to state-of-the-art computational capabilities, and you will be in contact with experts within ETH Zurich and worldwide.

Your profile

We are looking for a proactive and highly motivated candidate, with a MSc in a quantitative discipline (such as engineering, applied physics or mathematics) from an internationally recognized University and an excellent academic track record. Ideally, you have a background in quantitative modeling, optimization, and programming (e.g., Matlab, Python, Julia, GAMS). Knowledge of mixed-integer linear programming solvers (e.g., CPLEX, Gurobi, MOSEK), of modeling environments (e.g., Yalmip, Pyomo, CVX, CVXPY) and of uncertainty quantification are a plus.

You should be able to speak and write clearly in English. Furthermore, you will need to enjoy working in a competitive, dynamic, diverse, and international environment with other doctoral students and postdocs.

Interested?

We look forward to receiving your online application including the following documents:

  • CV
  • Transcripts of records for both BSc and MSC degrees
  • Contact information of at least two professional referees

Please note that we only accept applications which are submitted through our online application portal. We will not consider applications sent via email or postal services. Applications assessment will start immediately and will continue until the position is filled.

Further information about the Reliability and Risk Engineering Laboratory can be found on our website. Questions regarding the position should be directed by email to Prof. Dr. Giovanni Sansavini, sansavig@ethz.ch (no applications).

录取要求

  • We are looking for a proactive and highly motivated candidate, with a MSc in a quantitative discipline (such as engineering, applied physics or mathematics) from an internationally recognized University and an excellent academic track record.
  • Ideally, you have a background in quantitative modeling, optimization, and programming (e.g., Matlab, Python, Julia, GAMS).
  • You should be able to speak and write clearly in English.
  • Furthermore, you will need to enjoy working in a competitive, dynamic, diverse, and international environment with other doctoral students and postdocs.

申请亮点

  • Knowledge of mixed-integer linear programming solvers (e.g., CPLEX, Gurobi, MOSEK), of modeling environments (e.g., Yalmip, Pyomo, CVX, CVXPY) and of uncertainty quantification are a plus.

项目概览

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欧陆, 瑞士 所在地点
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截止日期 2021-08-21
苏黎世联邦理工

院校简介

苏黎世联邦理工是国际研究型大学联盟、全球大学高研院联盟、IDEA联盟成员,是闻名全球的世界顶尖研究型大学,连续多年位居欧洲大陆高校翘首。
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