A funded PhD position on Renewable Energy Forecasting is proposed among the Smart4RES consortium. The candidate will be based at the Centre PERSEE of MINES ParisTech.
In the context of the Smart4RES project, the research work will start with a literature review. The candidate will then familiarise with a portfolio of prediction models developed at MINES ParisTech and will carry out research on novel approaches i.e. based on AI. A number of test cases including heterogeneous types of data will be considered to evaluate the prediction models developed. The case of wind, solar, eventually run-of the river hydro, and aggregated production from virtual power plants will be considered to evaluate the proposed approaches.
A novel probabilistic forecasting approach for wind, PV and aggregated RES production. Evaluation results based on measured time-series from RES plants. A study on the incremental benefits in terms of performance brought by each source of data when considered as input to a model. A cost benefit analysis on the different sources of data (cost of data compared to the benefit
PROFILE OF THE CANDIDATE:
Engineer and / or Master of Science – 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. The desired profile should have a background in applied mathematics (statistics), data science, artificial intelligence and eventually electrical engineering. Skills in computer programming (eg MATLAB) are required. The candidate must be motivated to work in a team.
To apply please:
- Send your CV and motivation letter to firstname.lastname@example.org using as subject of your email « THESIS RESforecast 2020 PERSEE»,
- Fill in the on-line form: https://forms.gle/cVnraeTwRwv5Wmy19
Deadline for applications: 29/2/2020.
More information HERE.