Intelligent fault tolerant energy management system using first-price sealed-bid algorithm for microgrids

In the current landscape of the power industry, computer-based algorithms play a pivotal role in monitoring and controlling distributed energy resources. The prevalence of artificial intelligence algorithms has underscored the need for stability and fault tolerance in power systems, particularly in the realm of smart control, to prevent disruptions such as blackouts. This paper introduces a fault-tolerant multi-agent framework with a bottom-up approach designed for the control and management of energy flow within a Microgrid (MG). Within this framework, a tender system is implemented to effectively distribute tasks among agents. To incentivize power sharing among agents, an iterative first-price sealed-bid algorithm is employed, fostering a competitive environment within the multi-agent system (MAS) aimed at minimizing electricity costs in the MG. Each agent, functioning as a bidder, exercises autonomous decision-making, presenting its offer price to the tenderer during each time period to partake in the tender and secure rewards. The proposed framework not only facilitates power allocation but also integrates fault tolerance and system redevelopment capabilities. Theoretical analysis and empirical results affirm that the proposed approach yields a robust smart control system, ensuring stability, flexibility, and fault tolerance within the overall system. Simulation outcomes demonstrate that in instances where an agent encounters a fault, the demand can seamlessly be met by the remaining agents, thereby preserving the stability of the system.