Synergistic Cooperative control strategies for Electric Vehicles (EV) Charging Stations with Heterogeneous Energy Storage Systems (HESS)

Pervasive Technologies
Thesis Code: 
17001

Thesis Type: 6 months Master Thesis (Laurea Magistrale) for students in Electrical Engineering, Computer Engineering, Telecommunication Engineering, or related field.

Requirements:
- Experience with at least one programming language (e.g. Matlab, JAVA, Python,C++, etc.).
- Interest and/or previous knowledge of Artificial Intelligence, optimization techniques, Smart Grid, etc.

Description:
Motivation:
The growing number of Electric Vehicles (EV) circulating is resulting in a large number of EV charging stations being deployed in large cities and along major motorways. Such large deployment of high-consuming loads is expected to impact distribution grids, unless coordination and scheduling techniques are in place resulting in shifting and shaping loads due to EV charging whereas possible, as well as pointing users willing to charge EVs to the most suitable location. However, in order to be practically sustainable, such techniques need to be designed accounting for user needs in terms of time to charge and cost of energy. The emergence of large-scale Electric Storage System (ESS) may positively affect such scenario, by providing more flexibility.

Objective:
The goal of this thesis is to analyse and propose suitable control methods (e.g. heuristics, artificial intelligence,etc.) and architectures suitable to control in distributed fashion a network of EV charging stations supported by local ESS. Activities will include: studying the state of the art of control strategies and architecture for EV charging stations; designing and implementing mechanisms enabling efficient and stable EV charging station cooperation; analyzing performance of designed algorithms in established simulation tools (e.g. GridLab-D, openDSS). Scenarios, challenges and key reference standards for this thesis will be derived from the Storage4Grid EU project. The selected student will be tutored by researchers from the ISMB Pervasive Technologies Area and the Smart Energy Program.

Contacts: send a resume specifying the thesis code and title to pert@ismb.it.