Efficient load management in electric ships: A model predictive control approach

Nasibeh Zohrabi, Hasan Zakeri, Sherif Abdelwahed

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

This paper introduces a Model Predictive Control (MPC) approach for the Shipboard Power System (SPS) management under stressful high power loads. As part of the proposed approach, an optimization problem is formulated to mitigate the effects of a high power electrical load in the ship system and improve the overall system performance with respect to operating constraints. The nonlinear MPC also guarantees asymptotic stability of the closed-loop system by including a final cost in the objective function and a terminal inequality constraint. Moreover, a comparison of the controller performance under three different cases of load prediction, i.e. perfect prediction, no prediction and ARIMA prediction with different delays, is presented. In the case studies, a nonlinear model of Medium-Voltage DC shipboard power system is used for the control purpose. Simulation results illustrate the effectiveness of the presented MPC-based load management approach.

Original languageEnglish (US)
Title of host publication34th Annual IEEE Applied Power Electronics Conference and Exposition, APEC 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3000-3006
Number of pages7
ISBN (Electronic)9781538683309
DOIs
StatePublished - May 24 2019
Event34th Annual IEEE Applied Power Electronics Conference and Exposition, APEC 2019 - Anaheim, United States
Duration: Mar 17 2019Mar 21 2019

Publication series

NameConference Proceedings - IEEE Applied Power Electronics Conference and Exposition - APEC
Volume2019-March

Conference

Conference34th Annual IEEE Applied Power Electronics Conference and Exposition, APEC 2019
Country/TerritoryUnited States
CityAnaheim
Period3/17/193/21/19

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering

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