PhD on Synthetical data generation using multivariate models

1 week geleden

Eindhoven, Noord-Brabant, Nederland Eindhoven University of Technology Voltijd

Job Description

The project is centered around the generation of synthetic data, utilizing AI for state estimation, stochastic modeling, and reliability assessment, as well as grid-edge optimal solutions. These models will work in conjunction with AI-powered state estimations to improve network observability and grid monitoring. The integration of stochastic modeling and reliability assessment will offer valuable insights into how uncertainties impact grid reliability. Furthermore, with the implementation of edge intelligence, these advancements will enable optimal solutions for electricity grids in the Netherlands, and potentially other parts of Europe, all the while prioritizing user privacy.

The research outcomes will be promptly applied by Alliander for congestion estimation and flexibility procurement. As part of this project, all developed (AI-driven) models and algorithms will be integrated into production-ready open-source packages.

One of the key research tracks at AISO is as follows:

RT1: PhD in Synthetic Data Generation using Multivariate Models

This research will focus on a scalable approach by utilizing multivariate models to account for uncertainties in spatial-temporal correlations. It aims to merge top-down and bottom-up approaches into a scalable and reliable solution. The research will involve:

  • Requirement specifications for real-time state estimation and long-term power flow analysis
  • Designing algorithms that blend aggregated data with anonymized individual data
  • Validating the developed algorithms in a simulation environment with grid use-case scenarios
  • Integrating and validating solutions in a virtual grid environment

For information on the remaining three research tracks, please see below:

PhD2 / RT2: AI-driven State Estimation and Prediction
PhD3 / RT3: Stochastic Modelling and Reliability Assessment
PhD4 / RT4: Grid-Edge Optimal Solutions

Job Requirements

  • A Master's degree related to the modeling and analysis of power systems and distributed energy resources
  • A sound understanding of distribution grid planning and operation
  • Experience in data-driven modeling, probabilities, and stochastic optimization solutions is advantageous
  • Proficiency in scientific programming and/or numerical computing with languages like Python, Julia, or MATLAB is beneficial
  • Strong modeling skills in simulation tools such as PowerFactory or similar open-source power system packages. Experience in linking such simulation tools with MATLAB and/or Python programming environments is advantageous
  • Passion for open-source initiatives and willingness to develop basic skills in scientific software engineering
  • Capability to collaborate within an interdisciplinary team and engage with industrial partners
  • Desire to enhance teaching skills and mentor Master's and Bachelor's students
  • Fluency in spoken and written English (C1 level)
  • Knowledge of the Dutch language is a plus

Conditions of Employment

This position offers a meaningful role in a vibrant and ambitious university, within an interdisciplinary environment and a global network. You will be based on a picturesque, green campus conveniently close to the central train station. Additionally, we provide:

  • Full-time employment for four years, with an evaluative checkpoint after nine months. 10% of your time will be dedicated to teaching activities
  • Salary and benefits aligned with the Collective Labour Agreement for Dutch Universities, scale P (min. €2,770 max. €3,539)
  • Year-end bonus of 8.3% and annual vacation compensation of 8%
  • Access to top-tier training programs and support for personal development as an independent scientific researcher. At TU/e, we empower you to take ownership of your learning journey
  • Superior technical infrastructure, on-campus childcare facilities, and sports amenities
  • Allowance for commuting, home office, and internet expenses
  • Assistance from a dedicated Staff Immigration Team and a tax relief program (the 30% facility) for international candidates

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