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

doi:10.1007/s11708-023-0874-8

Front. Energy

2023, Vol. 17

Issue (2) : 198-210 https://doi.org/10.1007/s11708-023-0874-8

RESEARCH ARTICLE

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

Chunqiu XIA¹(

), Wei LI¹, Xiaomin CHANG¹, Ting YANG², Albert Y. ZOMAYA¹

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

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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.

Keywords energy management systems demand response scheduling under uncertainty renewable energy sources multiple-choice secretary algorithm

Corresponding Author(s): Chunqiu XIA

Online First Date: 09 May 2023 Issue Date: 29 May 2023

Cite this article:

Chunqiu XIA,Wei LI,Xiaomin CHANG, et al. A rank-based multiple-choice secretary algorithm for minimising microgrid operating cost under uncertainties[J]. Front. Energy, 2023, 17(2): 198-210.

URL:

https://academic.hep.com.cn/fie/EN/10.1007/s11708-023-0874-8
https://academic.hep.com.cn/fie/EN/Y2023/V17/I2/198

Fig.1 System overview.

Fig.2 Algorithm overview.

Fig.3 A simple example on how to find the best timings to reserve electricity for a task.

Fig.4 Three selections from an increasing candidate size (10 to 250) by RMSA.

Fig.5 Results by RMSA in box-plots.

Fig.6 Various selection amounts (15 to 300) from 1000 candidates by RMSA.

Fig.7 Performance comparison of different approaches at various schedule lengths.

Fig.8 Performance comparison at drastic fluctuating electricity price.

Fig.9 PAR comparisons.

Fig.10 Performance under peak limitation.

d_t	The total load demands at the time slot t
$η t$	The electricity unit price from external electricity resources at the time slot t
$δ t$	Electricity purchase from external resources at the time slot t
$Θ$	The set of all the load tasks
$τ i$	$τ i = {r i, e i, p i, d i}$ : $τ i$ denotes the task $i$ , with its release time $r i$ , execution time $e i$ , power consumption $p i$ , and absolute deadline $d i .$
$θ (τ i) (t)$	The status of the task $i$ at the time $t$ , $θ (τ i) (t) = 0$ means task $i$ is idle at the time $t$ while $θ (τ i) (t) = 1$ means task $i$ is executing at the time t.
$l t$	The total electricity load demands at the time slot t
$α t$	Total electricity generations from all the local DGs at the time slot t
$α t e$	Total efficient electricity generations from all the local DGs at the time slot t
$β c$	The battery capacity
$β t$	The battery storage at the time slot $t$ . The range is from the minimum $0$ to the maximum $β m a x$ .
$b t$	The battery utilization rate at the time slot $t$ . When its value is positive ( $b t ? 0$ ), the battery is charging at the moment; otherwise ( $b t < 0$ ), the battery is discharging at the moment.
$C (δ)$	The cost function representing the total operating cost of the microgrid

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