Master of Engineering Science
Electrical and Computer Engineering
The capabilities and potential of Model Predictive Control (MPC) based strategies for steam generator level (SGL) controls in nuclear power plants (NPPs) have been investigated. The performance has been evaluated for all operating conditions that also include start-ups, low power operations and load rejections. These evaluations have been done for MPC controllers based on existing advanced methodologies, as well as for any potential performance improvement that can be achieved by fine tuning some of the parameters (based on the characteristics of the SGL) of the existing MPC approaches.
Two version of MPC have been designed and implemented. The Standard MPC (SMPC) has investigated the performance of existing advanced MPC methodologies. The Improved MPC (IMPC) has investigated potential performance improvement over SMPC by selecting appropriate values in the weight matrix of the objective function.
Performance of MPC based approaches has been evaluated and compared with an optimized PI controller in term of i) set point tracking, ii) load-following, iii) transient responses, and iv) effectiveness subject to steam and feed water flow disturbances and feed water flow signal noise. The performance evaluation has been done through computer simulation, and also through simulation on a mock-up steam generator level system. The simulation results indicate strong potential for MPC based strategies, in particular for IMPC strategy, for effective control of the steam generator levels in nuclear power plants.
Taemiriosgouee, Ahmad, "Investigation of Model Predictive Control (MPC) for Steam Generator Level Control in Nuclear Power Plants" (2016). Electronic Thesis and Dissertation Repository. 4378.