Optimal Energy Management and MPC Strategies for Electrified RTG Cranes with Energy Storage Systems

Abstract

This article presents a study of optimal control strategies for an energy storage system connected to a network of electrified Rubber Tyre Gantry (RTG) cranes. The study aims to design optimal control strategies for the power flows associated with the energy storage device, considering the highly volatile nature of RTG crane demand and difficulties in prediction. Deterministic optimal energy management controller and a Model Predictive Controller (MPC) are proposed as potentially suitable approaches to minimise the electric energy costs associated with the real-time electricity price and maximise the peak demand reduction, under given energy storage system parameters and network specifications. A specific case study is presented in to test the proposed optimal strategies and compares them to a set-point controller. The proposed models used in the study are validated using data collected from an instrumented RTG crane at the Port of Felixstowe, UK and are compared to a standard set-point controller. The results of the proposed control strategies show a significant reduction in the potential electricity costs and peak power demand from the RTG cranes.

Publication DOI: https://doi.org/10.3390/en10101598
Divisions: College of Engineering & Physical Sciences
College of Engineering & Physical Sciences > School of Engineering and Technology > Mechanical, Biomedical & Design
Additional Information: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
Publication ISSN: 1996-1073
Last Modified: 10 Jun 2024 07:35
Date Deposited: 02 Aug 2019 09:34
Full Text Link:
Related URLs: http://www.mdpi ... 1073/10/10/1598 (Publisher URL)
PURE Output Type: Article
Published Date: 2017-10-13
Accepted Date: 2017-10-11
Authors: Alasali, Feras
Haben, Stephen
Becerra, Victor
Holderbaum, William (ORCID Profile 0000-0002-1677-9624)

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