EconPapers    
Economics at your fingertips  
 

Binary Grey Wolf Optimization Algorithm-Based Load Scheduling Using a Multi-Agent System in a Grid-Tied Solar Microgrid

Sujo Vasu (), P Ramesh Kumar and E A Jasmin
Additional contact information
Sujo Vasu: Department of Electrical and Electronics Engineering, Government Engineering College Thrissur, Affiliated to A P J Abdul Kalam Technological University, Thiruvananthapuram 695016, India
P Ramesh Kumar: Department of Electrical and Electronics Engineering, Government Engineering College Wayanad, Affiliated to A P J Abdul Kalam Technological University, Thiruvananthapuram 695016, India
E A Jasmin: Department of Electrical and Electronics Engineering, Government Engineering College Kozhikode, Affiliated to A P J Abdul Kalam Technological University, Thiruvananthapuram 695016, India

Energies, 2025, vol. 18, issue 16, 1-27

Abstract: Microgrids play a crucial role in the development of future smart grids, with multiple interconnected microgrids forming large-scale multi-microgrid systems that operate as smart grids. Multi-agent system (MAS)-based control solutions are the most suitable for addressing such control challenges. This paper presents a demand-side management (DSM) strategy using a meta-heuristic optimization technique for minimizing the household energy consumption cost using MAS. The binary grey wolf optimization algorithm (BGWOA) optimizes load scheduling, reducing electricity costs, without compromising consumer preferences using time-of-day (ToD) tariffs. The communication agents and load agents comprise the MAS used to streamline load control operations. The results demonstrate that MAS-based load control using metaheuristic optimization techniques enhances demand-side management, thus minimizing the electricity costs while adhering to contradictory parameters like user preferences, appliance duration, and load atomicity. This makes renewable energy integration more cost-effective in smart grids, thereby ensuring affordable, reliable, and sustainable energy for all.

Keywords: metaheuristic optimization; demand side management; microgrid; multiagent system; binary grey wolf optimization (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/1996-1073/18/16/4423/pdf (application/pdf)
https://www.mdpi.com/1996-1073/18/16/4423/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:18:y:2025:i:16:p:4423-:d:1727770

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().

 
Page updated 2025-08-22
Handle: RePEc:gam:jeners:v:18:y:2025:i:16:p:4423-:d:1727770