Operation Management of More-Electric Aircraft Using Two-stage Stochastic Model Predictive Control

Xin Wang, Najmeh Bazmohammadi, Jason Atkin, Serhiy Bozhko, Juan C. Vasquez, Josep M. Guerrero

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

2 Downloads (Pure)

Abstract

This paper proposes a two-stage stochastic model predictive control (SMPC) for the operation management of more electric aircraft (MEA). The goal is to minimize load shedding and switching activities in the system, considering the uncertainty of load profile, while optimally charging/discharging the battery-based energy storage system (BESS). In addition, several performance evaluation criteria are introduced to evaluate the effectiveness of the proposed approach. According to the results obtained in 50 random scenarios, SMPC leads to less load shedding time, higher stored energy levels, and lower uncertainty compensation costs compared to its deterministic counterpart.
Original languageEnglish
Title of host publication2023 25th European Conference on Power Electronics and Applications, EPE 2023 ECCE Europe
Publication dateSept 2023
Article number10264654
ISBN (Electronic)9789075815412
DOIs
Publication statusPublished - Sept 2023
Event2023 25th European Conference on Power Electronics and Applications (EPE'23 ECCE Europe) - Aalborg, Denmark
Duration: 4 Sept 20238 Sept 2023

Conference

Conference2023 25th European Conference on Power Electronics and Applications (EPE'23 ECCE Europe)
Country/TerritoryDenmark
CityAalborg
Period04/09/202308/09/2023

Keywords

  • Electrified aircraft
  • Energy management
  • Load scheduling
  • Model Predictive Control
  • Optimization

Fingerprint

Dive into the research topics of 'Operation Management of More-Electric Aircraft Using Two-stage Stochastic Model Predictive Control'. Together they form a unique fingerprint.

Cite this