Modeling Heterogeneous Energy Storage Systems (HESS) for Smart Grids Planning and Optimization

Pervasive Technologies
Thesis Code: 

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

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

Motivation: Electricity Storage System (ESS) at user premises and at substation level are quickly emerging as a reference solution for better exploiting Intermittent Renewable Energy Sources (RES). Due to the high market interest, a wide number of alternative technical solutions are being developed and deployed e.g. exploiting traditional and biological electro-chemical technologies, gas-to-power/power-to-gas technologies, mechanical systems, etc. Modeling and reliable prediction of expected behavior of the different ESS system is an important step to ensure that future investments in ESS systems are sustainable in the long-term.

Objective: The goal of this thesis is to develop ESS models which can be used to reliably evaluating and predicting performance of smart distribution grids where RES and heterogeneous ESS are deployed and operating in cooperative fashion. Expected activities include: studying the state of the art of predictable models for ESS; designing and implementing models mimicking and predicting behavior of ESS; evaluating the performance of proposed models in simulation tool (e.g. GridLab-D, openDSS) in smart grid planning scenarios. 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