Optimal power scheduling of seaport microgrids with flexible logistic loads

Sidun Fang, Chenxu Wang, Ruijin Liao, Changhong Zhao*

*Corresponding author for this work

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

66 Downloads (CityUHK Scholars)

Abstract

Seaports are progressively electrified to harness various energy resources to provide green logistic services to ships. They essentially act as multi-energy microgrids to enhance the energy efficiency and environmental sustainability of the maritime industry. This trend necessitates the coordinated operation of multiple sectors in seaport microgrids, which is a challenging problem due to the complex couplings of power, thermal, and fluid flows and the heterogeneity of logistic loads. An optimal power scheduling framework for seaport microgrids is developed. Specifically, a non-linear, non-convex optimisation problem is formulated to integrate various logistic loads, including cold ironing, quay and yard cranes, and reefer areas, in an unbalanced multi-phase power distribution network connected with a thermal network. The optimisation problem is solved in a scalable decomposed manner based on iterative convex relaxation and approximation. Simulation results on a real-world port model verify the efficacy of the proposed framework, as well as the potential of the flexible logistic loads in improving port energy efficiency.

Original languageEnglish
Pages (from-to)2711-2720
JournalIET Renewable Power Generation
Volume16
Issue number12
Online published24 Jan 2022
DOIs
Publication statusPublished - 7 Sept 2022
Externally publishedYes

Funding

Research Grants Council, University Grants Committee, Grant/Award Number: 24210220

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy
  2. SDG 9 - Industry, Innovation, and Infrastructure
    SDG 9 Industry, Innovation, and Infrastructure

Research Keywords

  • ENERGY EFFICIENCY
  • BERTH ALLOCATION
  • OPTIMIZATION
  • ASSIGNMENT
  • CRANES

Publisher's Copyright Statement

  • This full text is made available under CC-BY-NC-ND 4.0. https://creativecommons.org/licenses/by-nc-nd/4.0/

RGC Funding Information

  • RGC-funded

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