Organisation/Company: Mines Paris - PSL, Centre PERSEE
Research Field: Engineering Technology » Energy technology
Researcher Profile: Recognised Researcher (R2), Leading Researcher (R4), First Stage Researcher (R1), Established Researcher (R3)
Country: France
Application Deadline: 26 Dec 2024 - 22:00 (UTC)
Type of Contract: Temporary
Job Status: Full-time
Is the job funded through the EU Research Framework Programme? Not funded by a EU programme
Is the Job related to staff position within a Research Infrastructure? No
Offer Description Title: Optimization of flexibility services under multiple local uncertainties in the context of smart grids
Context and challenges:
In the context of the energy transition, power grids integrate massive amounts of renewable generation (mostly wind and solar) whose volatility and uncertainty bring unprecedented challenges to the grid operation. Flexible generation and demand, as well as storage or storage-like resources, are key for the efficient and reliable management of future power systems. The quest for flexibility is paramount at different temporal but also spatial scales and has expanded to multi-energy systems, e.g., the coupling between electrical and gas networks. Existing methodologies that propose flexibility indicators at a national level need to be revisited at the local level, by considering local characteristics and uncertainties in production and demand at a given territory.
Main objective of the thesis:
The overarching objective of this research project is to develop an approach for the optimal provision and use of flexibility at the level of a territory, which accounts for the uncertainties associated with local renewable production and local energy consumption of the potential flexible consumers (residential, commercial, industrial).
Methodology and expected results:
The first step of this research project is to define flexibility provision indicators, based on production/consumption adequacy and contextual assessment at the level of a territory, relying on predictive methodologies to quantify the local flexibility potential. These indicators will be used as inputs to produce a risk-aware analytical decision-aid methodology of flexibility valorization in multi-energy systems, employing forecasting models and optimization. The third step is to simplify the modelling chain by integrating forecasting and optimization via end-to-end learning of flexibility decisions based on AI.
Funding category: Autre financement public
Project: PEPR TASE "FLEX TASE"
PHD title: Doctorat en Énergétique et Procédés
PHD Country: France
Profile: Engineer and/or Master of Science degree (candidates may apply prior to obtaining their master's degree; the PhD will start after the degree is successfully obtained).
Good level of general and scientific culture. Good analytical, synthesis, innovation and communication skills. Qualities of adaptability and creativity. Motivation for research activity. Coherent professional project. Skills in programming (e.g., R, Python, Julia). A successful candidate will have a solid background in:
optimisation
electrical engineering
applied mathematics, statistics and probabilities, data science
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