EconPapers    
Economics at your fingertips  
 

Systems optimization model for energy management of a parallel HPGR crushing process

B.P. Numbi and X. Xia

Applied Energy, 2015, vol. 149, issue C, 133-147

Abstract: This work proposes a systems optimization control model for energy management of a parallel crushing process made up with high-pressure grinding rolls (HPGR) machines. The aim is to reduce both energy consumption and cost through optimal control of the process and load shifting, respectively. A case study of a copper crushing process is solved under three scenarios in order to evaluate the effectiveness of the developed model. Simulation results show that 41.93% energy cost saving is achieved through load shifting by coordinating the rotational speed of HPGRs. It is further shown that the energy saving can be achieved when the two HPGRs are not operated with equal overall efficiency, but also through a small decrement in rolls operating pressure. In the first case, 1.87% energy saving is obtained while in the last case, about 4.5% energy saving is achieved for every decrement of 0.2N/mm2 in rolls operating pressure without significant change in product quality.

Keywords: Systems optimization model; Energy management; Parallel HPGR crushing process; Time-of-use tariff (search for similar items in EconPapers)
Date: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0306261915004316
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:appene:v:149:y:2015:i:c:p:133-147

Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/bibliographic
http://www.elsevier. ... 405891/bibliographic

DOI: 10.1016/j.apenergy.2015.03.129

Access Statistics for this article

Applied Energy is currently edited by J. Yan

More articles in Applied Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().

 
Page updated 2025-03-19
Handle: RePEc:eee:appene:v:149:y:2015:i:c:p:133-147