Ao Zhang
PhD student at Harbin Engineering University, specializing in nuclear power system simulation, optimization, and prediction. Frequently uses Modelica and Python, primarily working with OpenModelica.
Session
System simulation is inherently an applied technology, driven by specific application demands. The Modelica language enables equation-based, system-level, multi-domain, and visual modeling, facilitating researchers conducting system simulation studies of nuclear power systems. This paper introduces the custom-built AESE library on the OpenModelica platform. Examples in AESE are provided to illustrate the development and simulation of system models for conventional pressurized water reactors (PWRs) and high-temperature gas-cooled reactors (HTGRs). The paper also describes tasks completed under different application scenarios, including hardware-in-the-loop simulation, multi-objective optimization, system identification, and rapid optimization, using model-driven and data-driven approaches with the AESE library. The further application of simulation models and data has significant practical and engineering value. This paper serves as a valuable reference for the intelligent application of energy system models in the context of advanced engineering challenges.