A Novel Approach to Multi-Agent Systems for Enhanced Decision Making and Optimization in Smart Grids

Abstract

Smart grids are becoming increasingly important as the demand for efficient energy management rises with the growing integration of renewable energy sources. Multi-agent systems (MAS) offer a promising approach for enhancing decision-making and optimization in smart grids due to their ability to manage complex systems with multiple autonomous entities. This paper introduces a novel approach to integrating multi-agent systems for optimizing decision-making in smart grid operations, particularly for load balancing, energy distribution, and fault detection. The proposed system uses a decentralized framework, where agents interact and cooperate to perform tasks such as power management and fault detection without the need for a centralized control unit. The paper discusses the architecture of the multi-agent system, the algorithms employed, and the results of simulations that demonstrate the potential of the system for enhancing grid efficiency. A comparison of the proposed system with traditional centralized approaches highlights the benefits of MAS in terms of scalability, reliability, and real-time adaptability. The results suggest that MAS can play a pivotal role in optimizing smart grid operations and contribute to the ongoing development of energy-efficient technologies.