News and Publications

11 April 2023

Interview with Mahsa Bagheri Tookanlou, RINA


Mahsa Bagheri Tookanlou, Power System Consultant, RINA Tech, UK. Mahsa has more than 6 years of experience in power systems consultancy and academia. She is a technically sound professional with proven track record of leading/contributing to smart grid R&D and industrial projects and delivering high quality reports/papers. She is experienced in optimisation of power system operation with integration of distributed energy resources, power system modelling and analysis, stochastic programming with applications to power systems, e-mobility ecosystem and electric vehicle scheduling, renewable energy integration within smart grids, energy management in smart grids, and electrical energy economics.


1. What is the role of your organisation in the TALENT project? What about your role?

RINA is responsible to do Task 7.2 regarding investigation on impacts of batteries connection on electrical grid for three different area (multi-home, district area, utility area). The role is leading Task 7.2, liaise with partners, collect data and information from partners, investigation the impacts of connection of batteries of multi-home, district area, and utility area on the electrical grids.

2. How do you see the cooperation between the project partners?

There have been some difficulties in data collection process. Due to jeopardising IP issue, the partners have not agreed to share the black boxes of battery models developed by them with RINA.

3. What challenges have you met during the work with the TALENT project and how did you overcome them?

Challenges of accessing to battery models:

To do Task 7.2, it has been required the black boxes of the power electronic models for batteries developed for multi-home, district, and utility area are provided for RINA. Getting the black boxes was so complicated because the partners were concerned about jeopardizing IP issues. Thus, RINA proposed that UNIOVI, CEA, and GaE generate the generic model for each area from data that can be extracted from the original models instead of sharing the black boxes. However, UNIOVI, CEA, and GaE have not generated neither the black boxes nor the generic models. In order to carry out Task 7.2, RINA generated the generic models for multi-home and utility area based on data and information mentioned in deliverables of control systems of batteries for multi-home and utility area. Since no information and report have been received for district area, RINA has not been able to carry out investigation on the impacts of proposed battery on the grid.

Challenges of data collection for electrical network:

Due to difficulties during the data collection process, benchmark electrical networks have been discussed and agreed with the partners.

4. What do you like more about TALENT?

The results obtained from Task 7.2 are interesting and show the contribution of TALENT solutions in maximising renewable resources integration into power systems, improvement in voltage and frequency stability during disturbances, and facilitation in black start. In the future, utilisation of TALENT solutions can be used for increasing green hydrogen exploitation into power systems.

5. What applications and benefits are expected to be achieved at the end of the project?

It is expected that TALENT battery will be installed in power systems to maximise the renewable energy resources exploitation, to facilitate black-start of the network, to improve the transient voltage stability of the networks during disturbances, and to respond quickly and properly to the frequency and voltage changes.

6. What is going to happen in the following months in your work?

Finding a solution to investigate on impacts of district area’s battery, if the black box of the battery is provided for RINA.

7. What positive impact did the project activities have in your organisation?

Finding solutions to meet RINA’s responsibilities for the project when there are some barriers and difficulties in having access to the prerequisites of the task.

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