An efficient scheduling approach for an iron-steel plant equipped with self-generation equipment under time-of-use electricity tariffs

被引:31
作者
Cao, Jianhua [1 ]
Pan, Ruilin [1 ,2 ]
Xia, Xue [1 ]
Shao, Xuemei [3 ]
Wang, Xuemin [1 ]
机构
[1] Anhui Univ Technol, Sch Management Sci & Engn, Maanshan 243032, Peoples R China
[2] Anhui Univ Technol, Anhui Higher Educ Inst, Key Lab Multidisciplinary Management & Control Co, Maanshan 243032, Peoples R China
[3] PHIMA Intelligence Technol CO Ltd, Maanshan 243032, Peoples R China
基金
中国国家自然科学基金;
关键词
Scheduling; Self-generation; Time-of-use electricity tariffs; Multi-objective mathematical model; Relationship propagation chain; The improved SPEA2; MULTIOBJECTIVE GENETIC ALGORITHM; BI-OBJECTIVE OPTIMIZATION; SINGLE-MACHINE; ENERGY-CONSUMPTION; COST; MAKESPAN; FLOWSHOP; MODEL; STATE;
D O I
10.1016/j.swevo.2020.100764
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Production scheduling under time-of-use electricity tariffs has become an efficient way for energy-intensive industries to decrease energy costs. However, when production tasks are over-concentrated in one scheduling cycle, the effectiveness of time-of-use electricity tariffs is no longer significant. This makes the introduction of self-generation power plant appealing for energy-intensive industries. This paper addresses an integrated scheduling problem from an iron-steel plant equipped with self-generation equipment under time-of-use electricity tariffs. In this problem, time-of-use electricity tariffs, the self-generation cost, and the on-grid electrovalence influence the total electricity cost simultaneously. A multi-objective mathematical model with energy-awareness is developed to optimize the production schedules and electricity cost jointly. An improved SPEA2 based on the relationship propagation chain is tailored for the problem, including scheduling solution encoding, crossover and mutation. A real-life case study from a Chinese iron-steel plant equipped with self-generation equipment demonstrates that the proposed methods can provide a high-quality scheduling scheme and the total electricity cost can be significantly reduced.
引用
收藏
页数:17
相关论文
共 42 条
[1]   Production scheduling optimisation with machine state and time-dependent energy costs [J].
Aghelinejad, MohammadMohsen ;
Ouazene, Yassine ;
Yalaoui, Alice .
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, 2018, 56 (16) :5558-5575
[2]  
[Anonymous], 2001, P EUROGEN 2001
[3]   Market share, market value and innovation in a panel of British manufacturing firms [J].
Blundell, R ;
Griffith, R ;
Van Reenen, J .
REVIEW OF ECONOMIC STUDIES, 1999, 66 (03) :529-554
[4]   Energy-conscious unrelated parallel machine scheduling under time-of-use electricity tariffs [J].
Che, Ada ;
Zhang, Shibohua ;
Wu, Xueqi .
JOURNAL OF CLEANER PRODUCTION, 2017, 156 :688-697
[5]   An Improved Model for Parallel Machine Scheduling Under Time-of-Use Electricity Price [J].
Cheng, Junheng ;
Chu, Feng ;
Zhou, Mengchu .
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING, 2018, 15 (02) :896-899
[6]   Bi-criteria single-machine batch scheduling with machine on/off switching under time-of-use tariffs [J].
Cheng, Junheng ;
Chu, Feng ;
Liu, Ming ;
Wu, Peng ;
Xia, Weili .
COMPUTERS & INDUSTRIAL ENGINEERING, 2017, 112 :721-734
[7]   BI-OBJECTIVE OPTIMIZATION OF SINGLE-MACHINE BATCH SCHEDULING UNDER TIME-OF-USE ELECTRICITY PRICES [J].
Cheng, Junheng ;
Chu, Feng ;
Chu, Chengbin ;
Xia, Weili .
RAIRO-OPERATIONS RESEARCH, 2016, 50 (4-5) :715-732
[8]   A fast and elitist multiobjective genetic algorithm: NSGA-II [J].
Deb, K ;
Pratap, A ;
Agarwal, S ;
Meyarivan, T .
IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION, 2002, 6 (02) :182-197
[9]   An Evolutionary Many-Objective Optimization Algorithm Using Reference-Point-Based Nondominated Sorting Approach, Part I: Solving Problems With Box Constraints [J].
Deb, Kalyanmoy ;
Jain, Himanshu .
IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION, 2014, 18 (04) :577-601
[10]   Parallel Machine Scheduling Under Time-of-Use Electricity Prices: New Models and Optimization Approaches [J].
Ding, Jian-Ya ;
Song, Shiji ;
Zhang, Rui ;
Chiong, Raymond ;
Wu, Cheng .
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING, 2016, 13 (02) :1138-1154