Multi-Agent Task Allocation to Minimize Costs of Energy Consumption in the Presence of a Price-Based Demand Response Program

• Type: Article in International Conference Proceedings Book
• Date: 2019

Authors

Ali B. Bahgat (Author) Other; Mohamed Lotfi (Author) Other; Omar M. Shehata (Author) Other; Elsayed I. Morgan (Author) Other; João P. S. Catalão (Author) FEUP

Conference proceedings International

Title: IECON 2019 - 45th Annual Conference of the IEEE Industrial Electronics Society

Pages: 4151-4156

Indexing

ISI Web of Knowledge - 0 Citations

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Other information

Authenticus ID: P-00S-1CW

DOI: 10.1109/iecon.2019.8926713

Abstract (EN): As a result of Demand Response (DR) programs implementation in the industrial sector, varying electricity prices based on Time-of-Use (ToU) rates are becoming more common, replacing traditional flate-rates per unit of energy consumption. On the other hand, increased automation of industrial facilities is gaining interest due to their reliability, flexibility, and robustness. However, it is necessary to determine a suitable task schedule in order to ensure their cost-efficiency and maximize profits. In this study, a Market-Based approach is considered to solve the Multi-Agent Task Allocation (MATA) problem for a group of homogeneous agents and tasks. While most previous studies model the problem considering flate-rates for electricity consumption, the main contribution of this study is accounting for the implementation of a DR program with varying ToU rates. The effects of optimizing the task allocation process on the costs incurred are investigated and compared to the effects of random assignment. Four different case studies are analyzed considering different-sized maps and number of tasks. The results show the computational efficiency of the proposed algorithm and its ability to massively decrease the electrical charging costs.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 6