کنفرانس مهندسی برق ایران

صفحه اصلی / سی و دومین کنفرانس بین المللی مهندسی برق

Controlling Energy Consumption and Intelligent Manufacturing through an Energy-aware Scheduling Algorithm in Industrial Sector

نویسندگان :

Negin Shafinezhad¹ Maryam Mahmoudi² Hamid Abrishami³ Vahid Baghishani⁴

1- دانشگاه فردوسی مشهد 2- دانشگاه فردوسی مشهد 3- دانشگاه فردوسی مشهد 4- شرکت توزیع برق خراسان

کلمات کلیدی :

Smart Grid (SG)،Demand Response (DR)،Scheduling،Industrial Customers،Energy Management System (EMS)

چکیده :

Uncontrolled energy consumption in the industrial sector, as the largest energy consumer in the Smart Grid (SG), presents several challenges. These challenges include the increased peak demand and high energy costs for industrial customers. To address these issues, the implementation of Demand Response (DR) programs can offer reliable and stable power to customers. Scheduling and adopting intelligent manufacturing techniques involve shifting process running times to off-peak periods and modifying consumption patterns in the production line. To achieve this goal, we propose an energy-aware scheduling method that focuses on decreasing energy consumption, particularly during peak hours, while also providing economic benefits through an energy storage system for industrial customers who voluntarily participate in the DR program. The proposed scheduling algorithm adjusts energy consumption based on the user-defined maximum consumption cost and coordinates processes according to their durations. We chose Additive Manufacturing (AM) as the case study to evaluate the effectiveness of the proposed method. The obtained results demonstrate an effective reduction in energy costs and peak hours, as well as a significant decrease in power demand during peak hours.

لیست مقالات

لیست مقالات بایگانی شده

Monte Carlo Analysis of Process Variations in Metal-Semiconductor-Metal Photodetectors for Nanophotonic Interconnects Application

Arash Qodratnama - Farshad Khunjush - Mohsen Raji

Data Association and Multi-Target Localization Using Particle Swarm Optimization

Seyed Mohammad B. Seyedin - Fereidoon Behnia

پیش‌بینی توان تولیدی توربین‌های بادی با روش‌های حافظه کوتاه‌مدت طولانی و ماشین تقویت‌کننده‌ی گرادیان سبک

سید متین ملکوتی - مهدی منصوری - امیر ریخته گرغیاثی

Implementation of an Optimized Deep Learning Model to Assess Pediatric Sleep Apnea Severity Using SpO2 Signals on Resource-Limited Microcontrollers

Erfan Mortazavi - Hanieh Mohammadi - Bahram Tarvirdizadeh - Khalil Alipour - Mohammad Ghamari

A Novel Multi-Variable Search Space Method for Selective Harmonic Control-PWM in Active Power Filters

Mohammadhossein Mohammadpour - Faegheh Taghipour Reyneh - Hoda Ghoreishy - Seyyed Asghar Gholamian

RQA-based EEG Analysis for Assessing Motor Hand Recovery in Children with Hemiparetic CP After Interactive Rehabilitation Protocol: A Case Study

Parisa Hosseini - Shahed Salehzehi - Ali Koohian Mohammad abadi - Zahra Sadeghi - Fatemeh Karimzadeh - Mohammad Ebrahim Hashemi - Hamid Reza Kobravi - Mehran Beiraghi Toosi - Narges Hashemi - Javad Akhondian

جایابی بهینه نیروگاه های مقیاس کوچک و منابع تولید توان راکتیو بمنظور افزایش پایداری ولتاژ شبکه انتقال و فوق توزیع خوزستان

مسعود بشیرپور - کیومرث زمانی - محدثه مولایی - امید سروری

Perfect Tracking of a Non-minimum Phase MIMO System

Saeedreza Tofighi - Farshad Merrikh-Bayat

Effect of Physical Characteristics on Artiﬁcial Neural Network Error Reduction for Indoor Propagation Modeling

SeyedehMounes Eslami - Amir Ahmad Shishegar

تشخیص و مقیاس بندی شدت افسردگی براساس روش‌های یادگیری ماشین و با استفاده از معیار‌های خطی، غیرخطی و آماری محاسبه شده در سیگنال‌های الکتروانسفالگرام

پریسا رئوف امامزاده هاشمی - وحید شالچیان - رضا رستمی

بیشتر