Multi-objective optimization and decision-making in the context of complex and multi-physical systems/processes

Abstract

The global energy sector is undergoing rapid changes from generation through fossil fuel sources (example : coal, oil and gas) to generation through Renewable Energy Sources (example : wind power and solar power). Hybrid Battery-Solar-Wind Power Generation Systems (HBSWPGS) are highly unstable due to the fluctuation of the output power generated by the system caused by instantaneous variations in the availability of solar and wind energy, making the output power an uncertain variable. This thesis intends to evaluate the influence of uncertainty and produce a risk analysis of each constituent subsystem, namely the Wind Turbine Generator (WTG), the Photovoltaic Generator (PVG) and Battery Energy Storage System (BESS) to provide quantified uncertainty information to aid in the decision-making process in designing an optimal configuration of an HBSWPGS. The electrical performance parameters of the subsystems are modeled as a function of environmental variables such as wind speed, solar radiation and ambient temperature. We model the uncertainty of the generated power and evaluate the sensitivity of the electrical parameters to describe their influence on the performance of hybrid system as a function of the variation of weather conditions throughout the hours of the day