LAUSR

ABSTRACT A fundamental understanding of the sizing process is a key element for sizing affordable, reliable, and sustainable nano/micro-off-grid systems. Nevertheless, the openness and transparency of modeling approaches are still low and open-source tools are scarce in this field. In this study, an open-source modeling tool for the optimization of renewable nano/micro-off-grid power supply systems is developed. System component models based on datasheets consider dynamic and time-dependent influencing factors. The modeling tool uses a multi-objective optimization based on the Non-Sorting-Genetic-Algorithm-II aiming at minimizing costs and load outage. For a better understanding of the sizing process, the influence of temporal resolution, simulation period, and location on the Pareto-optimal fronts is analyzed. The system location and by that irradiance, ambient temperature, and wind speed shows to be the strongest influence factor, which leads up to 2-5 times higher costs for achieving the same security of energy supply. While a higher temporal resolution increases the costs and load outages due to a more realistic illustration of energy production and demand, a shorter simulation period shows an increase in the system costs but a reduction of load outages because of the non-observance of component replacement, its cost reduction, and degradation.