Multi-agent-based collaborative regulation optimization for microgrid economic dispatch under a time-based price mechanism

Abstract

• This paper provides a multi-agent based coordinated dispatch strategy for the economic dispatch of the microgrid under a time-based price mechanism. • We develop a microgrid optimization model for the microgrid operation process, which includes battery regulation and user satisfaction. • The established optimization model is solved using a MACPSO algorithm, and the agent communication mechanism in the microgrid is examined. • The performance comparison using different algorithms (PSO, IPSO, MAPSO and MACPSO) has been presented. • The proposed multi-agent coordinated dispatch strategy is validated by designing a multi-agent system simulation environment and using the Java agent development (JADE) framework. The economic optimal dispatch of a microgrid is a challenging task with significant economic and social implications. Under a time-based price mechanism, this paper proposes a multi-agent-based coordinated dispatch strategy for the microgrid's economic dispatch. The information between the agents in the microgrid can be fed back in time to reduce microgrid operation failures by coordinated control between the demand-side load, the battery, and the power generation side micro-sources. The output of other micro-sources is then coordinated using an appropriate battery charging and discharging plan based on the characteristics of the time-based electricity price mechanism. Following that, an economical microgrid operation model is established and solved using a multi-agent chaotic particle swarm optimization (MACPSO) algorithm, which considers user satisfaction. Finally, a multi-agent system (MAS) simulation environment is built using the Java agent development (JADE) framework. The proposed microgrid with multi-agent coordinated control can effectively improve its operation efficiency, according to a comparative analysis of examples.