Demand Response Potential Assessment of Steel Plant Based on Refined Simulation

• Published in: 2023 7th International Conference on Power and Energy Engineering (ICPEE) pp. 303 - 309
• Main Authors: Zou, Bokang, Zhang, Yuanshi, Chen, Qirui, Ding, Yiyuan, Yu, Xiaorong, Hu, Qinran, Wang, Qi
• Format: Conference Proceeding
• Language: English
• Published: IEEE 22.12.2023
• Subjects: Costs; Direct reduction of iron; Electricity; Energy consumption; Flexibility; Furnaces; industrial production control; Job shop scheduling; Nonlinear programming model; Production; Programming; steel industry
• DOI: 10.1109/ICPEE60001.2023.10453848

The steel industry has witnessed a progressive increase in the electrification degree of its production process due to advancements in decarburization technology. Consequently, there will be a substantial rise in electricity usage within the steel sector. The transition in energy consumption patterns is a significant obstacle to the functioning of the power system. One of the potential methods for achieving zero-carbon steel manufacturing is through the utilization of the direct reduction iron (DRI) - electric arc furnace (EAF) production route. This particular route is characterized by its high energy consumption and intricate production load characteristics. This paper attempts to examine the demand response capabilities of power loads throughout the DRI-EAF production process. A nonlinear programming model, encompassing the DRI-EAF steel plant, is constructed in light of the dependency of each link in the DRI-EAF production process. This study aimed to examine the impact of various production plans on the possible demand response of hydrogen-based steel plants, with a focus on minimizing the operating costs of these mills. The findings indicate that the scheduling model proposed in this study effectively utilizes the scheduling benefits offered by adjustable resources in the iron and steel production process, hence facilitating the economic scheduling of iron and steel plants.