کنفرانس مهندسی برق ایران

صفحه اصلی / سی و چهارمین کنفرانس بین المللی مهندسی برق

Stochastic Optimal scheduling in the Cement Industry with the Aim of Reducing Electricity Bills and Environmental Emissions

نویسندگان :

Mostafa Darvishi¹ Ehsan Shokouhmand² Mehrdad Tahmasebi³

1- Department of Electrical Engineering, Il.C. Islamic Azad University Ilam, Iran 2- Department of Electrical and Computer Engineering Jundi-Shapur University of Technology Dezful, Iran 3- Department of Electrical Engineering, Il.C. Islamic Azad University Ilam, Iran

کلمات کلیدی :

Cement industry،energy imbalance،energy market،renewable energy sources،solar cells،demand response

چکیده :

In recent years, the challenge of energy imbalance has evolved into a significant barrier to maintaining stable and uninterrupted production within the cement industry. In this context, the imbalance between power generation and demand has resulted in frequent outages, disruptions in industrial production cycles, and substantial economic losses. Given the challenges of energy imbalance, pollutant emissions, and global warming, power plants based on renewable energy sources are increasingly being developed by industries. In this regard, Article 16 of the “Knowledge-Based Production Leap Act” mandates that industries with electricity consumption exceeding 1 MW supply renewable energy sources with at least 1% of their electricity demand. This approach not only diversifies the energy portfolio of cement companies and reduces operational costs but also contributes to the mitigation of environmental pollutant emissions. Therefore, this paper examines the daily operation of solar cells using the proposed computational approach and compares it with alternative electricity supply methods, such as purchases from the energy market. Additionally, the optimal production schedule of the cement units was determined using the load response method to minimize costs. The results of the case study indicate that combining the capabilities of solar power plants with load response can reduce costs and emissions by 29% and 3%, respectively.