Research on Energy Optimal Scheduling Based on Supply and Demand Forecast for Iron and Steel Enterprises

被引：1

作者：

Dai Haibo ^{[1
]}

Zhu Weifeng ^{[1
]}

机构：

[1] Huazhong Univ Sci & Technol, Wuhan 430074, Hubei, Peoples R China

来源：

2014 SIXTH INTERNATIONAL CONFERENCE ON MEASURING TECHNOLOGY AND MECHATRONICS AUTOMATION (ICMTMA) | 2014年

关键词：

energy utilization; optimal scheduling; supply and demand forecast; iron and steel; system engineering;

D O I：

10.1109/ICMTMA.2014.123

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Iron and steel enterprises energy system structure is complex, there are many different kinds of energy medium, and different degree of correlation between each medium. Therefore, how to make efficient and reasonable use of all kinds of energy, improve the efficiency of energy utilization, become one of the important problems to be solved in the iron and steel enterprises. In this paper, the energy cost control and optimal scheduling problem is described with mathematical model from the perspective of system engineering, the energy scheduling model is proposed based on supply and demand forecast, and an example is given to verify the feasibility of this model.

引用

页码：502 / 505

页数：4

共 6 条

[1] Univariate modeling and forecasting of monthly energy demand time series using abductive and neural networks
Abdel-Aal, R. E.
[J]. COMPUTERS & INDUSTRIAL ENGINEERING, 2008, 54 (04) : 903 - 917
[2] Guo T X, 2010, HIGH TECHNOLOGY IND, V12, P40
[3] Hao Y S, 2013, METALLURGICAL IND AU, V37
[4] Lu Z W, 2013, ENG SCI, V04, P23
[5] Trend time-series modeling and forecasting with neural networks
Qi, Min
Zhang, G. Peter
[J]. IEEE TRANSACTIONS ON NEURAL NETWORKS, 2008, 19 (05): : 808 - 816
[6] Prediction of energy demands using neural network with model identification by global optimization
Yokoyama, Ryohei
Wakui, Tetsuya
Satake, Ryoichi
[J]. ENERGY CONVERSION AND MANAGEMENT, 2009, 50 (02) : 319 - 327

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