Model and Algorithm for Planning Hot-Rolled Batch Processing under Time-of-Use Electricity Pricing
Batch-type hot rolling planning highly affects electricity costs in a steel plant, but previous research models seldom considered time-of-use (TOU) electricity pricing. Based on an analysis of the hot-rolling process and TOU electricity pricing, a batch-processing plan optimization model for hot rol...
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doaj-314237ad92ea431faa73409e0e0358fa2020-11-25T01:12:56ZengMDPI AGProcesses2227-97172020-01-01814210.3390/pr8010042pr8010042Model and Algorithm for Planning Hot-Rolled Batch Processing under Time-of-Use Electricity PricingZhengbiao Hu0Dongfeng He1Wei Song2Kai Feng3Department of Ferrous Metallurgy, School of Metallurgical and Ecological Engineering, University of Science and Technology Beijing, Beijing 100083, ChinaDepartment of Ferrous Metallurgy, School of Metallurgical and Ecological Engineering, University of Science and Technology Beijing, Beijing 100083, ChinaDepartment of Ferrous Metallurgy, School of Metallurgical and Ecological Engineering, University of Science and Technology Beijing, Beijing 100083, ChinaDepartment of Ferrous Metallurgy, School of Metallurgical and Ecological Engineering, University of Science and Technology Beijing, Beijing 100083, ChinaBatch-type hot rolling planning highly affects electricity costs in a steel plant, but previous research models seldom considered time-of-use (TOU) electricity pricing. Based on an analysis of the hot-rolling process and TOU electricity pricing, a batch-processing plan optimization model for hot rolling was established, using an objective function with the goal of minimizing the total penalty incurred by the differences in width, thickness, and hardness among adjacent slabs, as well as the electricity cost of the rolling process. A method was provided to solve the model through improved genetic algorithm. An analysis of the batch processing of the hot rolling of 240 slabs of different sizes at a steel plant proved the effectiveness of the proposed model. Compared to the man−machine interaction model and the model in which TOU electricity pricing was not considered, the batch-processing model that included TOU electricity pricing produced significantly better results with respect to both product quality and power consumption.https://www.mdpi.com/2227-9717/8/1/42hot rollingtou electricity pricinghot rolling planninggenetic algorithm |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Zhengbiao Hu Dongfeng He Wei Song Kai Feng |
spellingShingle |
Zhengbiao Hu Dongfeng He Wei Song Kai Feng Model and Algorithm for Planning Hot-Rolled Batch Processing under Time-of-Use Electricity Pricing Processes hot rolling tou electricity pricing hot rolling planning genetic algorithm |
author_facet |
Zhengbiao Hu Dongfeng He Wei Song Kai Feng |
author_sort |
Zhengbiao Hu |
title |
Model and Algorithm for Planning Hot-Rolled Batch Processing under Time-of-Use Electricity Pricing |
title_short |
Model and Algorithm for Planning Hot-Rolled Batch Processing under Time-of-Use Electricity Pricing |
title_full |
Model and Algorithm for Planning Hot-Rolled Batch Processing under Time-of-Use Electricity Pricing |
title_fullStr |
Model and Algorithm for Planning Hot-Rolled Batch Processing under Time-of-Use Electricity Pricing |
title_full_unstemmed |
Model and Algorithm for Planning Hot-Rolled Batch Processing under Time-of-Use Electricity Pricing |
title_sort |
model and algorithm for planning hot-rolled batch processing under time-of-use electricity pricing |
publisher |
MDPI AG |
series |
Processes |
issn |
2227-9717 |
publishDate |
2020-01-01 |
description |
Batch-type hot rolling planning highly affects electricity costs in a steel plant, but previous research models seldom considered time-of-use (TOU) electricity pricing. Based on an analysis of the hot-rolling process and TOU electricity pricing, a batch-processing plan optimization model for hot rolling was established, using an objective function with the goal of minimizing the total penalty incurred by the differences in width, thickness, and hardness among adjacent slabs, as well as the electricity cost of the rolling process. A method was provided to solve the model through improved genetic algorithm. An analysis of the batch processing of the hot rolling of 240 slabs of different sizes at a steel plant proved the effectiveness of the proposed model. Compared to the man−machine interaction model and the model in which TOU electricity pricing was not considered, the batch-processing model that included TOU electricity pricing produced significantly better results with respect to both product quality and power consumption. |
topic |
hot rolling tou electricity pricing hot rolling planning genetic algorithm |
url |
https://www.mdpi.com/2227-9717/8/1/42 |
work_keys_str_mv |
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