The main goal of this project is to develop artificial intelligence (AI) based tools for modelling and analysis of the future energy systems, including intermittent renewables, storage systems and the dispatchable energy units to meet the expected demand side requirements. This is achieved by utilizing real or simulated plant data from multilevel (from small to large-scale units) intermittent and displatchable supply units, combined with other inputs such as operational conditions, demand patterns and market price. The developed tools will be used to conduct scenario based techno-economic analysis of aggregated energy systems for real time applications to meet the energy demand. These tools will provide inputs to support optimum management of high level aggregated energy systems, taking into account various factors such as plants’ availability, operational condition, degradation etc. A specific case study incorporating different supply units in an aggregated level will be created to examine the performance of the developed tools. This project aims at providing a generic approach for optimum management of energy systems, using the real-time capability of AI based solutions and ICT technologies.
This project will develop knowledge and tools for modeling and real-time optimum management of future aggregated energy systems using AI techniques.
The research work of the PhD candidate will focus on:
- Identification of appropriate intelligent technologies and evaluation of their applicability for modeling of energy systems
- Identification and use of suitable open source tools/software
- Collection and utilization of experimental and simulated data in collaboration with international partners of the project to evaluate and validate the developed tools
- Real-time techno-economic analysis of the aggregated energy systems
Planned secondments: ARGE Netz (Germany), Scottish Power Energy Network (United Kingdom), University of Edinburgh (United Kingdom).
Lead supervisor(s): Professor Mohsen Assadi. Co-supervisor: Homam Nikpey, PhD.