Model predictive control of a Lab-Scale thermal energy storage system in RELAP5-3D

Abstract

Increased renewable energy penetration of an electrical grid generally creates more supply fluctuations. Traditional base-load systems, such as nuclear power, can be retrofitted with thermal energy storage (TES) systems to meet supply demand fluctuations. These systems can store energy during low electricity demand times to allow the reactor to operate at constant power while simultaneously fluctuating electricity output. The control of these systems is of vital importance and Model Predictive Control (MPC) is a leading control mechanism for optimized production plans with forecast information. This study combines high fidelity RELAP5-3D models with MPC to control an experimental benchtop system that approximates expected nuclear power thermal-hydraulics. RELAP5-3D is a high-fidelity code utilized for thermal–hydraulic phenomenon simulations for nuclear applications. The United States Nuclear Regulatory Commission (NRC) has supported the use of this code for licensing purposes. The NRC requires in depth testing before nuclear plants can be built or changed. The use of MPC with RELAP5-3D is used here to demonstrate the potential of a lab-scale TES coupled with a high-fidelity thermal–hydraulic model for use in the NRC licensing process.