Due to the advancing digitalization, which also affects the energy systems, an unprecedented level of information technology networking is being achieved step by step.
In the SINERGY WP5 framework, three workshops a combination of training courses and lectures, hands-on experience, social and networking activities are foreseen. The goal is to increase the competence level of PhD students and other interested stakeholders in the domain of the SINERGY project.
The work package 4 is specifically dedicated to ensuring the involvement of IMP’s early-stage researchers in terms of providing adequate support by strategic partners as part of their training and (co-)mentoring activities. Hence, different staff exchange activities were conducted in the project framework. While in the first reporting period, this WP was affected by the COVID measures, in the years 2022 and 2023 the staff exchange activities continued as planned in the GA.
The aim of work package 4 is to coordinate the Sinergy activities on staff exchange and training. Though the first half of the project was heavily affected by the COVID-19 pandemic the project team managed to fulfill the training plan using webinar technologies. The deliverable reports the performed activities and exchanges for the project duration January 2021 to March 2022 which includes:
The main objective of SINERGY work package 3 is to establish collaboration with strategic partners, i.e. AIT and NUIG, and enable expertise and “know-how” exchange in the area of smart grids, distributed energy resources, building optimization and building information modelling.
Smart Energy Management refers to a variety of novel concepts and technologies, serving at both energy generation and consumption side, such as energy efficiency, demand management, Smart Grid, micro-grids, renewable energy sources, and other emerging solutions. It represents one of the fastest developing fields, according to the EU priorities, while, at the same time, it remains somewhat neglected in the South-eastern Europe countries.
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 952140.
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