Peak-load management in steel plants

Peak-load management in steel plants Mini steel-plants in India, using electric-arc furnaces for steel manufacturing, are highly energy intensive. In the context of increasing electricity prices and the introduction of time varying electricity rates by utilities, mini steel-plants can reschedule their operations to reduce their electricity bills. This paper presents a load model, which incorporates the characteristics of batch-type loads common to any type of process industry. The model is coupled with an optimisation formulation utilising integer programming for minimising the total electricity-cost satisfying production, process flow and storage constraints for different tariff structures. The methodology proposed can be used for determining the optimal response for any industry under time varying tariffs. The case study of a steel plant shows that significant reductions in peak-period demand (about 50%) and electricity cost (about 5.7%) are possible with optimal-load schedules. The utility can also get significant reduction in the peak coincident demand if large industries optimally reschedule their productions in response to time-of-use (TOU) tariff. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Applied Energy elsevier

Peak-load management in steel plants

Applied Energy, Volume 83 (5) – May 1, 2006

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Publisher
Elsevier
Copyright
Copyright © 2005 Elsevier B.V.
ISSN
0306-2619
D.O.I.
10.1016/j.apenergy.2005.05.002
Publisher site
See Article on Publisher Site

Abstract

Mini steel-plants in India, using electric-arc furnaces for steel manufacturing, are highly energy intensive. In the context of increasing electricity prices and the introduction of time varying electricity rates by utilities, mini steel-plants can reschedule their operations to reduce their electricity bills. This paper presents a load model, which incorporates the characteristics of batch-type loads common to any type of process industry. The model is coupled with an optimisation formulation utilising integer programming for minimising the total electricity-cost satisfying production, process flow and storage constraints for different tariff structures. The methodology proposed can be used for determining the optimal response for any industry under time varying tariffs. The case study of a steel plant shows that significant reductions in peak-period demand (about 50%) and electricity cost (about 5.7%) are possible with optimal-load schedules. The utility can also get significant reduction in the peak coincident demand if large industries optimally reschedule their productions in response to time-of-use (TOU) tariff.

Journal

Applied Energyelsevier

Published: May 1, 2006

References

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