Multi-Agent Systems for Resource Allocation and Scheduling in a Smart Grid

• Published in: Sensors (Basel, Switzerland) Switzerland), 2022-10, Vol.22 (21), p.8099
• Main Authors: Binyamin, Sami Saeed, Ben Slama, Sami
• Format: Article
• Language: English
• Subjects: Alternative energy sources; Civil engineering; commercial buildings; Communication; Complex systems; Computer Communication Networks; Consumption; Coordination; Decision making; Demand side management; distributed systems; Electric vehicles; Electricity; Electricity distribution; Energy efficiency; Energy management; Energy resources; Infrastructure; Methods; Multi-agent systems; Network reliability; Regulation; Renewable resources; Reproducibility of Results; residential buildings; Resource Allocation; Review; Scheduling (Management); smart grid; Smart grid technology; Sustainability
• ISSN: 1424-8220; 1424-8220
• DOI: 10.3390/s22218099

Multi-Agent Systems (MAS) have been seen as an attractive area of research for civil engineering professionals to subdivide complex issues. Based on the assignment's history, nearby agents, and objective, the agent intended to take the appropriate action to complete the task. MAS models complex systems, smart grids, and computer networks. MAS has problems with agent coordination, security, and work distribution despite its use. This paper reviews MAS definitions, attributes, applications, issues, and communications. For this reason, MASs have drawn interest from computer science and civil engineering experts to solve complex difficulties by subdividing them into smaller assignments. Agents have individual responsibilities. Each agent selects the best action based on its activity history, interactions with neighbors, and purpose. MAS uses the modeling of complex systems, smart grids, and computer networks. Despite their extensive use, MAS still confronts agent coordination, security, and work distribution challenges. This study examines MAS's definitions, characteristics, applications, issues, communications, and evaluation, as well as the classification of MAS applications and difficulties, plus research references. This paper should be a helpful resource for MAS researchers and practitioners. MAS in controlling smart grids, including energy management, energy marketing, pricing, energy scheduling, reliability, network security, fault handling capability, agent-to-agent communication, SG-electrical cars, SG-building energy systems, and soft grids, have been examined. More than 100 MAS-based smart grid control publications have been reviewed, categorized, and compiled.