Design concept for optimizing the renewable micro-generation technologies to supply and off-grid community energy demand

Jeroen van Hellenberg Hubar (Eindhoven University of Technology)

For fulfilling the energy demand of an off-grid community it is important first to specify this demand. The required type of energy (electrical and/or thermal), amount of energy and the duration of energy demand are important parameters and dependent on the comfort level and the geographical location of the community. This graduation project is an attempt to come up with a design concept to supply this demanded energy with an optimal sustainable energy mix.









This research is aimed towards creating a design concept for an off-grid community, which has an optimized energy system with 100% renewable micro-generation technologies. The renewable energy technologies satisfy the electrical and thermal energy demand. Meanwhile the comfort level of the inhabitants for an off-grid community is ensured. To demonstrate the design concept, a case study of a hypothetical campground located on the island of Texel in the Netherlands is performed. Annual energy demand profiles with hourly results are created and considered as input for the simulation model in TRNSYS. The energy technologies are modified into decision variables and defined in the optimization software modeFRONTIER, resulting in 2000 renewable energy technology system configurations. After post processing and considering the stakeholders perspectives, one configuration was chosen as the most favourable. Uniform Latin Hypercube sampling (ULH) is chosen as DOE and Multi Objective Genetic Algorithm, MOGA-II as optimizer.  The proposed concept is valid for each type of off-grid community and energy technology configuration, since these can be defined in the literature research.

While generating the energy profiles and modeling the simulation and optimization model, the designer should keep all the possible energy technology configurations open. In such a way no choices, even unaware, are made between energy system configurations which bound the energy system optimization space. In this way a full spectrum optimization with independent energy technologies can be achieved in future research, and ideal decision making will be enhanced.