1. Project description:

This project aims at developing new methods to analyse the intrinsic uncertainty of the renewable energies, e.g., solar photovoltaics and wind power, and develop models for optimal energy allocation and pricing. This post would be suitable for applicants with general interest in machine learning, optimisation, smart grid, and computational statistics.

Specific tasks for the research assistant include (but not limited to):

• Modelling and simulating domestic/non-domestic electricity demand profiles and renewable energy generation profiles using AI models (e.g., GAN) and state-of-the-art physics models.
• Using techniques from game theory and market design to develop the optimal allocation model and dynamic pricing scheme for renewable energy.
• Direct contribution to the coding using Python, MATLAB, or R.
• Contributing to paper writing.

This project is funded by the PVC (Research) Strategic Fund 2021/22, University of Essex.

2. Project objectives:

• Develop a new retail pricing scheme for energy retailers.
• ESS capacity/sizing problem with given wind&PV plants.

3. Useful dataset:

• SmartMeter Energy Consumption Data in London Households
• Renewable Energy Planning Database (REPD) ****
• Wind Energy Projects in London
• Hourly weather data in London
• Photovoltaic (PV) Solar Panel Energy Generation data
• Photovoltaic Geographical Information System