Distributed energy resources optimisation

An urban or domestic district energy system typically consists of micro wind turbines (WT), PV panels, heat pumps (HP) and vehicle to grid (V2G) system for the residents. This project aims to study the V2G, WP, HP, WT, PV system integration to meet the energy demand for a residential area. Th use of AI can optimise the operation of the energy network from ideal utilization of the accessible assets and the effectiveness of operations.

DER systems typically use renewable energy sources, including small hydro, biomass, biogas, solar power, wind power, and geothermal power, and increasingly play an important role in the electric power distribution system. The aim of this project is to predict the power requirements, renewable power generation and plan the conventional power generation and dispatch. AI will be used to optimise and plan the power generation and distribution.

In this project, the student will be developing a model of the local power distribution system including local renewable energy systems. The model includes the power generation, power storage and utilisation by the domestic area, then the model will be used to simulate the network and optimise the generation/storage of power throughout the day. AI optimisation algorithms will be used (GA, PSO, ACO, etc) to optimise the operation of the network at the peak and off-peak hours.

The student should have knowledge in power systems simulation, knowledge of programming language is required, such a MATLAB, Python, as well as knowledge of power system simulation packages such as DigSilent power factory.

How to apply

If you are interested in applying for the above PhD topic please follow the steps below:

1. Contact the supervisor by email or phone to discuss your interest and find out if you woold be suitable. Supervisor details can be found on this topic page. The supervisor will guide you in developing the topic-specific research proposal, which will form part of your application.
2. Click on the 'Apply here' button on this page and you will be taken to the relevant PhD course page, where you can apply using an online application.
3. Complete the online application indicating your selected supervisor and include the research proposal for the topic you have selected.

Good luck!

This is a self funded topic

Brunel offers a number of funding options to research students that help cover the cost of their tuition fees, contribute to living expenses or both. See more information here: https://www.brunel.ac.uk/research/Research-degrees/Research-degree-funding. The UK Government is also offering Doctoral Student Loans for eligible students, and there is some funding available through the Research Councils. Many of our international students benefit from funding provided by their governments or employers. Brunel alumni enjoy tuition fee discounts of 15%.

Meet the Supervisor(s)

Maysam Abbod - Education - Dr Maysam F. Abbod (MIET, CEng, SMIEEE, SFHEA) He received BSc degree in Electrical Engineering fromUniversity of Technology in 1987. PhD in Control Engineering fromUniversity ofSheffield in 1992. From 1993 to 2006 he was with the Department of Automatic Control and Systems Engineering at theUniversity of Sheffield as a research associate and senior research fellow

Related Research Group(s)

Brunel Interdisciplinary Power Systems - Power systems analysis for transmission and distribution networks, smart grids; congestion monitoring in transmission networks; simulation and analysis of new energy markets; optimisation of the design and operation of electrical networks; condition monitoring of power station and power system plant; energy-efficient designs for underground electric power cables.