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Distributed Cluster Cooperation for Multiple DC MGs Over Two-Layer Switching Topologies

Xiaoqing Lu, Jingang Lai

2020IEEE Transactions on Smart Grid40 citationsDOI

Abstract

To improve power supply reliability when enabling energy exchange among multiple dc microgrids (MGs) as well as effectively avoid overload or uncertainty, this paper presents a distributed cluster cooperation strategy through establishing a master-slave control framework over two-layer switching topologies. According to the physical cluster structure of multiple dc MGs, all distributed generators (DGs) within each dc MG cluster are divided into one master-DG and multiple slave-DGs. All master-DGs, allowed to information interaction among multiple MG clusters, constitute the master control layer; whereas slave-DGs, enabled to information exchange within each MG cluster, then together form the slave control layer. Once the stable operation is realized among all master-DGs, the stability of all slave-DGs can be automatically driven by their respective master-DGs. Eventually the weighted average voltage of all DGs can be regulated to their references, meanwhile, the accurate current sharing can be simultaneously realized not only within each dc MG cluster but also among multiple dc MG clusters. All controllers are fully distributed and can be applied in all sparse two-layer switching network topologies, control time constant related sufficient conditions are also derived to ensure the whole system stability. The effectiveness of the results is verified through different cases in MATLAB/SimPowerSystems.

Topics & Concepts

Network topologyCluster (spacecraft)Computer scienceReliability (semiconductor)Layer (electronics)Topology (electrical circuits)MATLABStability (learning theory)VoltagePower (physics)Control (management)Control theory (sociology)Distributed computingEngineeringComputer networkElectrical engineeringMaterials sciencePhysicsArtificial intelligenceQuantum mechanicsComposite materialOperating systemMachine learningMicrogrid Control and OptimizationSmart Grid Energy ManagementOptimal Power Flow Distribution
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