Title :
MPC-based power management in the shipboard power system
Author :
Paran, S. ; Vu, T.V. ; El Mezyani, T. ; Edrington, C.S.
Author_Institution :
Electr. & Comput. Eng., Florida State Univ., Tallahassee, FL, USA
Abstract :
This paper represents the development of an intelligent control by applying model predictive control to the power management of a DC-based ship system. In a shipboard power system, the control approach should ensure optimal load sharing among generators while maintaining the DC bus voltage stability. Model predictive control is a promising optimal control which has been proven to be efficient and robust for dynamic systems. Model predictive control is applied in order to meet the load centric energy/power demand. It will provide a predictive and adaptive approach to energy/power management routines. The algorithm and method are presented and validated through simulation in MATLAB/Simulink and PLECS.
Keywords :
demand side management; energy management systems; intelligent control; marine power systems; optimal control; power system stability; predictive control; ships; voltage control; DC bus voltage stability; DC-based ship system; MPC-based power management; Matlab; PLECS; Simulink; adaptive approach; dynamic systems; energy management; intelligent control; load centric energy demand; load centric power demand; model predictive control; optimal control; optimal load sharing; predictive approach; shipboard power system; Cost function; Generators; Marine vehicles; Power generation; Power systems; Predictive control; Microgrid; model predictive control; particle swarm optimization; power management;
Conference_Titel :
Electric Ship Technologies Symposium (ESTS), 2015 IEEE
Conference_Location :
Alexandria, VA
Print_ISBN :
978-1-4799-1856-0
DOI :
10.1109/ESTS.2015.7157855
