RESEARCH ARTICLE

A rank-based multiple-choice secretary algorithm for minimising microgrid operating cost under uncertainties

  • Chunqiu XIA , 1 ,
  • Wei LI 1 ,
  • Xiaomin CHANG 1 ,
  • Ting YANG 2 ,
  • Albert Y. ZOMAYA 1
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  • 1. Centre for Distributed and High Performance Computing, School of Information Technologies, The University of Sydney, Camperdown, NSW 2006, Australia
  • 2. School of Electrical Automation and Information Engineering, Tianjin University, Tianjin 300072, China
E-mail: chunqiu.xia@sydney.edu.au

Received date: 31 Jul 2022

Accepted date: 22 Feb 2023

Published date: 15 Apr 2023

Copyright

2023 Higher Education Press 2023

Abstract

The increasing use of distributed energy resources changes the way to manage the electricity system. Unlike the traditional centralized powered utility, many homes and businesses with local electricity generators have established their own microgrids, which increases the use of renewable energy while introducing a new challenge to the management of the microgrid system from the mismatch and unknown of renewable energy generations, load demands, and dynamic electricity prices. To address this challenge, a rank-based multiple-choice secretary algorithm (RMSA) was proposed for microgrid management, to reduce the microgrid operating cost. Rather than relying on the complete information of future dynamic variables or accurate predictive approaches, a lightweight solution was used to make real-time decisions under uncertainties. The RMSA enables a microgrid to reduce the operating cost by determining the best electricity purchase timing for each task under dynamic pricing. Extensive experiments were conducted on real-world data sets to prove the efficacy of our solution in complex and divergent real-world scenarios.

Cite this article

Chunqiu XIA , Wei LI , Xiaomin CHANG , Ting YANG , Albert Y. ZOMAYA . A rank-based multiple-choice secretary algorithm for minimising microgrid operating cost under uncertainties[J]. Frontiers in Energy, 2023 , 17(2) : 198 -210 . DOI: 10.1007/s11708-023-0874-8

Notations

dtThe total load demands at the time slot t
ηtThe electricity unit price from external electricity resources at the time slot t
δtElectricity purchase from external resources at the time slot t
ΘThe set of all the load tasks
τiτi={ri,ei,pi,di}: τi denotes the task i, with its release time ri, execution time ei, power consumption pi, and absolute deadline di.
θ(τi)(t)The status of the task i at the time t, θ(τi)(t)=0 means task i is idle at the time t while θ(τi)(t)=1 means task i is executing at the time t.
ltThe total electricity load demands at the time slot t
αtTotal electricity generations from all the local DGs at the time slot t
αteTotal efficient electricity generations from all the local DGs at the time slot t
βcThe battery capacity
βtThe battery storage at the time slot t. The range is from the minimum 0 to the maximum βmax.
btThe battery utilization rate at the time slot t. When its value is positive (bt0), the battery is charging at the moment; otherwise (bt<0), the battery is discharging at the moment.
C(δ)The cost function representing the total operating cost of the microgrid
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