Optimizing Load Dispatch in Iron and Steel Enterprises Aligns with Solar Power Generation and Achieves Low-Carbon Goals

Samrawit Bzayene Fesseha (), Bin Li, Bing Qi, Songsong Chen and Feixiang Gong
Additional contact information
Samrawit Bzayene Fesseha: School of Electrical and Electronic Engineering, North China Electric Power University, Beijing 102206, China
Bin Li: School of Electrical and Electronic Engineering, North China Electric Power University, Beijing 102206, China
Bing Qi: School of Electrical and Electronic Engineering, North China Electric Power University, Beijing 102206, China
Songsong Chen: Beijing Key Laboratory of Demand Side Multi-Energy Complementary Optimization and Supply-Demand Interaction Technology, China Electric Power Research Institute Co., Ltd., Beijing 100035, China
Feixiang Gong: Beijing Key Laboratory of Demand Side Multi-Energy Complementary Optimization and Supply-Demand Interaction Technology, China Electric Power Research Institute Co., Ltd., Beijing 100035, China

Energies, 2025, vol. 18, issue 17, 1-15

Abstract: This study develops an optimization-based scheduling framework for coordinating the energy-intensive operations of a steel enterprise with estimated solar power availability. Unlike prior approaches that focus primarily on process efficiency or carbon reduction in isolation, the proposed model integrates demand response with linear programming to improve solar utilization while respecting load priorities. The solar generation profile is derived from typical meteorological year (TMY) irradiance data, adjusted for panel efficiency and system parameters, thereby serving as an estimated input rather than measured data. Simulation results over a 31-day horizon show that coordinated scheduling can reduce grid dependence and increase solar energy utilization by up to 99% under the simulated conditions. While the findings demonstrate the potential of load scheduling for industrial decarbonization, they are based on estimated solar data and a simplified system representation. Future work should incorporate real-world solar measurements and stochastic models to address uncertainty and further validate industrial applicability.

Keywords: energy optimization; solar power utilization; grid independence; iron and steel industry; decarbonization (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/1996-1073/18/17/4662/pdf (application/pdf)
https://www.mdpi.com/1996-1073/18/17/4662/ (text/html)

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:gam:jeners:v:18:y:2025:i:17:p:4662-:d:1740636

Access Statistics for this article

Energies is currently edited by Ms. Cassie Shen

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().