| description abstract | Abstract. Hybrid energy systems (HES) entail the integration of various electricity-generating technologies (such as natural gas, wind, nuclear, etc.) and storage systems (such as thermal, battery electric, hydrogen, etc.). Such integration efforts, particularly when focused on identifying superior configurations, face challenges in determining the optimal storage sizing and dynamic behavior and necessitates an adaptable and efficient evaluation framework. Driven by such needs in both early system concept development and retrofit efforts, this work outlines a versatile computational framework for efficiently assessing the net present value of various integrated generator/storage technologies with a general optimization model. The subsystems’ fundamental dynamics are defined, with a particular emphasis on balancing critical physical and economic domains to enable optimal decision-making in the context of control co-design (CCD). In its presented form, the framework formulates a linear dynamic optimization problem that can be efficiently solved through a direct transcription approach. The CCD optimization problem of an HES for 30 years with an hourly mesh can be solved in less than 1800 s, depending on the case study. Three case studies focusing on natural gas with thermal storage and carbon capture, wind energy with battery storage, and nuclear with hydrogen are selected to demonstrate the framework’s capabilities in formulating a wide range of HES problems in the context of CCD and dynamic optimization, highlighting its value in facilitating the techno-economic assessment of various HES configurations. | |
