Architecture of Energy Conservation in the Iron and Steel Enterprises Based on Internet of Things

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Abstract:

The management of saving energy is a weak link of Chinese industrial energy conservation at present. Modern industrial enterprise energy system shows characteristics as followed: the multielement of energy mediathe complication of Energy equipmentEnergy demand more targetingthe networking of Energy supply. The new change of system put forward the new requirements to the energy management. Due to early of energy management system (EMS) is focus on energy data acquisition and centralized monitoring, and the deep analysis of the energy system is not enough, so it can't use the useful information from energy data mining effectively, especially the optimization of energy use, and can not meet the requirements of it. The paper create the architecture energy conservation of Industry entirety, based on the pan under the environment of network, under the background of informationization and industrialization depth fusion iron and steel enterprises , Promoting the change of energy production and utilization means, making progress in comprehensive utilization of resources Energy conservation and emissions reduction, etc..

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1205-1208

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September 2013

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© 2013 Trans Tech Publications Ltd. All Rights Reserved

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[1] K. Hiroshi. Production and technology of iron and steel in JaPanduring 2005[J], ISIJ International, 2006, 46(7): 939-958.

Google Scholar

[2] R.J. Stark, Computerized energy management in an integrated steel Plant[C]. Proceedings of the American Control Conference, CA, USA, 1984: 638-643.

Google Scholar

[3] B. Ramani T.S. Subramonian. Energy management system in Bhilai steel Plant-implementation and future enhancements[J]. Electricity Conservation Quarterly, 1997, 18(2): 3-9.

Google Scholar

[4] R. Valsalam,N. Klishnan,V. Muralidharen. Energy management and control system for integrated steel Plants[C]. Proceedings of the National Convention on Computerisation and Automation in steel Industry, Ranchi, India, 1996: 59-83.

Google Scholar

[5] Lahhinen, Seppo. Implementation of an energy management system as strategic investment[J]. International Paperworld IPW, 2009, 42(5): 6-8.

Google Scholar

[6] K. eho,T. Hong,C. Hyun. Integrated schedule and cost model for repetitive construction Proeess[J]. Journal of management in Engineering, 2010, 26(2): 78-88.

DOI: 10.1061/(asce)me.1943-5479.0000009

Google Scholar

[7] P. Sukumaran, THong,M. Hastak. Validation of a model for Predicting sehedule changes in highway work zones [J]. Journal of TransPortation in Engineering, 2006, 132(8): 638-648.

DOI: 10.1061/(asce)0733-947x(2006)132:8(638)

Google Scholar

[8] S.G. kim,Y.J. Koo H.Y. Kim. Optimization of pumping schedule based on forecasting the hourly water demand in Seoul [J]. Water Science & Technology: Water Supply, 2007, 7(5): 85-93.

DOI: 10.2166/ws.2007.112

Google Scholar

[9] P. Sukumaran, THong,M. Hastak. Validation of a model for Predicting sehedule changes in highway work zones[J]. Journal of TransPortation in Engineering, 2006, 132(8): 638-648.

DOI: 10.1061/(asce)0733-947x(2006)132:8(638)

Google Scholar

[10] C. Dao Manh, K. Myung Kyun, Real-Time Communications on an Integrated Fieldbus Network Based on a Switched Ethernet in Industrial Environment, Embedded Software and Systems, vol. 4523, pp.498-509, (2007).

DOI: 10.1007/978-3-540-72685-2_47

Google Scholar

[11] O. Lida,Y. Ushijima,T. Sawada. Application of AI techniques to blast furnace operation[J]. Iron and Steel Engineer, 1995, (10): 26-29.

Google Scholar

[12] T. Nagatani. Dynamical model for retrieval of tram schedule [J]. Physica A: Statistical Mechanics and its Application, 2007, 377(2): 661-671.

DOI: 10.1016/j.physa.2006.11.029

Google Scholar