Thesis subject

Data-driven simulation platform of solar energy potential in Dutch farms

Level: MSc

Research area/discipline: Simulation Modelling, Data Science for Sustainability

Prerequisites: Programming in Python (INF-22306) and/or Software Engineering (INF-32306)

Short description:

Both European and Dutch climate policies have dictated that serious efforts should be made to reduce carbon emissions and increase the share of renewable energy in order to mitigate climate change and meet the targets of Paris climate agreement1 .
This has led to a rapid development and application of renewable energy technologies across all sectors. In the Netherlands, there is a clear objective towards an increased electronification and sustainability in the agriculture sector, according to the Dutch climate agreement in 20192 .
In the agriculture sector, and motivated by some policy incentives, this trend has manifested itself by an increasing deployment of Photovoltaic (PV) systems on land, buildings or greenhouses rooftops.
This thesis will look at the solar PV energy production potential in this sector using data science and machine learning approaches. The final aim is to develop a data-driven simulation platform that enables to assess solar PV energy production potential in Dutch farms.


The work in this master thesis entails:

  1. To collect data, analyze and create an overview of the available and potential rooftop for solar PV panels installation in the agriculture sector in the Netherlands, focusing on buildings and greenhouses rooftops in farms.
  2. To develop a simulation platform that enables to

    • assess energy generation potential of those PV systems using a data-driven approach.
    • evaluate the electricity demand that can be fulfilled by those systems.

Required skills/knowledge:

Programming in Python, basic data analytics and GIS maps, interest about sustainability and energy transition.

Relevant literature:

  • Hassanien, Reda Hassanien Emam, Ming Li, and Wei Dong Lin. "Advanced applications of solar energy in agricultural greenhouses." Renewable and Sustainable Energy Reviews 54 (2016): 989-1001.
  • Wang, Tianyue, et al. "Integration of solar technology to modern greenhouse in China: Current status, challenges and prospect." Renewable and Sustainable Energy Reviews 70 (2017).
  • Litjens, G. B. M. A., et al. "A spatio-temporal city-scale assessment of residential photovoltaic power integration scenarios." Solar Energy 174 (2018): 1185-1197.

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) | |


1) The Paris Agreement, 2015,

2) National Climate Agreement (The Netherlands), 2019,