Thesis subject

Energie handelsplatform Roosendaal (MSc)

A feasibility study of flexible energy assets in a (semi) rural energy hubs

Short description

Energy cooperation ‘Energie handelsplatform Roosendaal’ or EHP Roosendaal (Energy trading platform Roosendaal) is a local community comprised of farmers and small/medium business owners in Roosendaal. Their ultimate goal is to provide business park ‘Majoppeveld’ in Roosendaal with clean energy year round. When looking into the issue of providing clean energy for the business park, the business owners at Majoppeveld quickly realised they wouldn’t be able to provide the renewable energy production capacity themselves, simply because of insufficient room to place solar panels or wind turbines. At this point, contact was made with the local agriculture organisation (ZLTO) division to see if farmers surrounding the business park could supply surplus solar energy to the business park. Soon after the idea for a local energy trading platform was borne and is currently organised in a local energy cooperation assisted by a technical energy trading provider ‘All in power’. The energy cooperation currently consist of 25 net energy consumers (mostly small/medium businesses) and 12 net energy producers (mostly farmers). Currently 1000 MWh’s of electricity is supplied locally where the goal is to grow to 25.000 MWh.

This 1000 MWh’s are renewables produced per annum though, and there is still a strong dependency on the national energy market because all locally produced power is currently solar. This means on sunny days, an energy surplus to the national market exists and the deficient in winter and at night times are also satisfied from that market. As the national energy market is currently very volatile, the small business owners and farmers are incentivised to decrease this dependency because a volatile market poses a costs risk. This can be achieved by better matching local supply and demand which can be achieved by diversification of local energy sources (e.g. add wind to the mix) or by employing flexible assets at farms/businesses or on a community level. In this study, we would like to assess the feasibility of several flexibility options at farm/business or community level. The objective is to simulate if the flexible assets are costs effective (is there a business case?) in reducing the market dependency within EHP Roosendaal.

Real consumption and feed-in data (15 or 60 minutes interval for a year), for both power and gas, will be available from the businesses/farms involved in the project. Also an energy tariff scheme will be provided.


  1. Determine energy flexibility options at farm/business or community level in rural energy hubs
  2. Build a simulation model for those assets both at business/farmer level, and at community level (energy cooperative)
  3. Simulate the effects of flexible assets on the costs of energy within energy cooperation EHP Roosendaal in order to determine the feasibility of deployment of such assets. The objective is to minimize the energy costs of the community caused by the link with the national market.
  4. Analysis and discussion of results


The work in this MSc thesis entails:

  • To interview business owners/farmers about feasible flexible assets that already exist or could be implemented on site and their technical specifications and user preferences
  • To interview the energy cooperation ‘EHP Roosendaal’ about possible shared assets that could be employed by the cooperation
  • A little market research on flexible energy assets and their specs (in collaboration with business/farm owners)
  • Analysis and structuring of energy consumption and production data available within ‘EHP Roosendaal’
  • Develop a mathematical optimization model in order to simulate the effects of flexible assets on the total energy costs in the energy community


    • Courses: Programming in Python (INF-22306), Decision Science (Operations Research/Mathematical Optimization Models). Optional: Machine Learning (FTE-35306)
    • Required skills/knowledge: Programming knowledge, experience with time series (no requirements on specific tool/language). Knowledge/interest about the energy market and how it functions.

    Contact person(s)
    Tarek Alskaif (

    Sander van der Stelt (ZLTO) (