Research area/discipline: Smart Systems Design, Data Science for Sustainability
Prerequisites: Programming in Python (INF-22306), Big Data (INF-34306), Data Science Concepts (INF-34306) (or Machine Learning (FTE-35306))
Microgrids can be conceived as integrated operational and technological systems that help in optimizing sustainable power generation, distribution, and consumption. The concept refers to a set of energy consumption units and distributed energy resources operating as a single controllable system that provides power to its local area. Microgrids can have two different modes of operation: the islanded mode and the grid-connected mode. The design of microgrids typically comprise an Information and Communication Technologies (ICT)-based infrastructure capable of measuring and monitoring a multitude of parameters, such as power usage and generation, as well as enabling data exchange between the components and with the involved stakeholders in an efficient, secure and reliable manner.
In the agriculture sector, microgrids can have high potential in improving power security, resilience, sustainability and efficiency, where power demands of farming activities and infrastructure (e.g., greenhouses, irrigation, animal farms, in-door farms) can be locally matched with low carbon and renewable energy sources. The proposed master thesis project will investigate the different needs for microgrids in the agriculture sector and propose an ICT-system design, integrated with big data systems, for microgrids operation in farming infrastructure.
The work in this master thesis entails:
- To assess the potential needs for microgrids in the agriculture sector.
- To perform a systematic literature review on the different ICT systems design for data collection, processing, analytics and exchange between different systems components in microgrids.
- To investigate the potential and challenges of big data applications in microgrids.
- To develop and propose an ICT system design for microgrids in farming infrastructure.
Programming in Python, big data analytics, interest about sustainability, energy transition and smart grids.
- Moharm, Karim. "State of the art in big data applications in microgrid: a review." Advanced Engineering Informatics 42 (2019): 100945.
- Hirsch, Adam, Yael Parag, and Josep Guerrero. "Microgrids: A review of technologies, key drivers, and outstanding issues." Renewable and sustainable Energy reviews 90 (2018): 402-411.
- Zia, Muhammad Fahad, Elhoussin Elbouchikhi, and Mohamed Benbouzid. "Microgrids energy management systems: A critical review on methods, solutions, and prospects." Applied energy 222 (2018): 1033-1055.
For more information:
For making an appointment to discuss the thesis topic, please send an email to: Dr.Ir. Tarek AlSkaif | Assistant Professor | Information Technology group (INF) | Wageningen University & Research (WUR) | https://www.wur.nl/en/Persons/Tarek-dr.-T-Tarek-Alskaif.htm | email@example.com