DOI: 10.5281/zenodo.18137232
title: Industrial Energy Load Dataset from a Large-Scale Steel Plant in Tianjin, China

description: This dataset supports the research presented in the manuscript:  “Optimizing Load Dispatch in Iron and Steel Enterprises Aligns  with Solar Power Generation and Achieves Low-Carbon Goals”, published in MDPI, Energies (2025) - (https://www.mdpi.com/1996-1073/18/17/4662)

Data Collection

The data for this study were gathered using a combination of online and offline industry screening methods, ensuring a comprehensive and efficient collection of relevant information.

Online Data Collection: Various online methods were employed to gather foundational information about the industry operations. These included the following:

·         System Inquiries: Accessing user systems remotely to retrieve data such as wiring diagrams and power loads.

·         Telephone Inquiries: Conduct interviews to clarify operational details and verify available energy data.

·         Questionnaires: Distributing structured questionnaires to gather insights into the following:

–           User wiring diagrams.

–           Historical power loads.

–           Major energy-consuming equipment.

–           Historical responses to energy management programs, such as demand response events.

These methods provided a robust dataset of basic operational information to frame the analysis.

Offline On-Site Investigation: To acquire a deep understanding of the energy usage pattern and operational flexibility, in-person investigations were conducted at the industry sites of Jiangsu company in Tianjin Province. These investigations focused on the following:

·         Energy Consumption Profiles: Measuring and recording the energy consumption of various equipment.

·         Production Control Systems: Examining internal production systems to evaluate how energy usage aligns with production schedules.

·         Adjustable Capacity Analysis: Assessing the actual flexibility in the production line and equipment to determine the potential for load adjustments.

This detailed on-site assessment ensured that the collected data accurately reflected real-world operations and capabilities.

Data overview 

This dataset comprises time-series data collected at 15-min intervals over 31 days, sourced from the iron and steel industry in Jiangsu Province, Tianjin.

The dataset is organized into two key components that are critical for optimization operations in the iron and steel industry:

1.         User gate load data: This section captures the total power demand or energy consumption across two primary processes:

·         Ironmaking processes: Transformation of raw materials into molten iron.

·         Steelmaking processes: Convert molten iron into finished steel products.

These datasets refer to the total power demand for the iron and steel plants at the interface point between the industrial facility and the power grid.

2.         User loop load data: The details of the power consumption of individual workshops and equipment within the ironmaking and steelmaking processes. These are the following:

·         Ironmaking Smart Factory Sintering Workshop 111: Handles the sintering of raw iron ore.

·         Steelmaking New Fourth Furnace Workshop 113: Comprising subcomponents:

–           Blast Furnace Body

–           Blast Furnace Pumping Station

–           Fan

·         Steelmaking II Workshop 114: Includes rolling mill and casting machine

·         Steelmaking I Workshop 118: Includes rolling mill and casting machine

·         Electric furnace: Engaging in steel melting operations

·         Carrier machine: Engaging in steel melting operations