Development of optimal stressor scenarios for new operational energy systems

Abstract

This thesis leverages a previously developed and tested simulation model for operational energy related systems in order to develop better stressor scenarios for acceptance testing. Analyzing the previous model using a design of experiments (DOE) and regression analysis provides critical information about the associated operational environment factors and their relationships that directly affected system performance. A nearly orthogonal Latin hypercube (NOLH) is used to expeditiously and effectively understand the entirety of the scenario space. This experimentation method identifies the most stressful combinations of the operational factors that can be used to test system performance. Under these maximally severe scenarios, a revised set of system requirements emerge from experimentation. The resulting system requirements can be used to revisit the design requirements and develop a more robust system. This process can be adopted by testing and acceptance agencies to further examine new technologies.