Title :
Distributed Optimal Resource Management Based on the Consensus Algorithm in a Microgrid
Author :
Yinliang Xu ; Zhicheng Li
Author_Institution :
Sun Yat-sen Univ.-Carnegie Mellon Univ. Joint Inst. of Eng., Sun Yat-sen Univ., Guangzhou, China
Abstract :
A microgrid is a promising approach to provide clean, renewable, and reliable electricity by integrating various distributed generations and energy storage systems into power systems. However, highly intermittent renewable generations and various load demands pose new challenges to the optimal resource management in a microgrid. This paper proposes a fully distributed control strategy based on the consensus algorithm for the optimal resource management in an islanded microgrid. The proposed strategy is implemented through a multiagent system framework, which only requires information exchange among neighboring agents through a local network. The objective is achieved through a two-level control strategy. The upper control level is a consensus-based optimization algorithm that discovers the reference of optimal power generation or demand while maintaining the supply-demand balance. The lower control level is responsible for reference tracking of the associated component. Simulation results in the IEEE 14- and 162-bus systems are presented to demonstrate the effectiveness of the proposed control strategy.
Keywords :
distributed control; distributed power generation; multi-agent systems; optimisation; power distribution control; power distribution faults; power generation control; IEEE 14-bus systems; IEEE 162-bus systems; consensus-based optimization algorithm; distributed control; distributed optimal resource management; information exchange; islanded microgrid; multiagent system framework; optimal power generation; reference tracking; supply-demand balance; two-level control; Algorithm design and analysis; Cost function; Decentralized control; Microgrids; Propagation losses; Reliability; Resource management; Consensus algorithm; islanded microgrid; optimal resource management; renewable generation (RG);
Journal_Title :
Industrial Electronics, IEEE Transactions on
DOI :
10.1109/TIE.2014.2356171