Stochastic decision-making framework: uncertainty versus controllability of Distributed Energy Sources
Project Leader: Maria Vrakopoulou
Primary Contact: Maria Vrakopoulou (firstname.lastname@example.org)
Keywords: Distribution Networks; optimisation; renewable energy
Disciplines: Electrical & Electronic Engineering
Power systems are facing a challenging transition with the amount of Distributed Energy Resources (DERs) rapidly increasing. DER is bringing uncertainty in the operation mainly through the forecast error of the production of Renewable Energy Sources eg, solar panels. This may initiate operational decisions that are not either optimised in the most efficient way or they are rendering the system to a reliability risk, eg, the probability of blackout or load shedding is high. On other hand, DER may increase the controllability of the system via storage devices eg, batteries, or also via demand response mechanisms. If this controllability is utilised in a co-ordinated and sophisticated way, the negative uncertainty impact on power system operation can be significantly reduced.
This PhD project will develop a stochastic optimisation/control framework that aims in the most economic system operation that welcomes the maximum RES penetration. While taking into account the system uncertainty, the framework will obtain as an output the system operational decisions in different time scales, i.e. dispatch of resources, reserve power provision, real-time control, accompanied with metrics that describe the reliability risk of the system.
This is a multidisciplinary project that lives in the interplay of power systems, optimisation, control, probability theory and machine learning. Interested students with an excellent background at least in 3 out of the 5 fields are encouraged to apply.
The project is fully funded for 3.5 years with around $30k net income per year and a performance-based top-up of up to $5k. The starting date can be flexible.