Microgrid Energy Management With Asynchronous Decentralized Particle Swarm Optimization

• Published in: IEEE access Vol. 9; pp. 69588 - 69600
• Main Authors: Perez-Flores, Alejandro C., Antonio, Jesus D. Mina, Olivares-Peregrino, Victor Hugo, Jimenez-Grajales, Humberto R., Claudio-Sanchez, Abraham, Ramirez, Gerardo Vicente Guerrero
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2021; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Bandwidths; Clusters; Communication channels; Control stability; Distributed generation; Energy management; Energy sources; Jacobian matrices; Low voltage; Microgrids; Multilayers; Optimization; Particle swarm optimization; Resource management; smart grids; Systems stability; Tariffs
• ISSN: 2169-3536; 2169-3536
• DOI: 10.1109/ACCESS.2021.3078335

Controlling distributed energy resources (DERs) in low voltage microgrids is a challenging task for operators. The simultaneous operation of independent small-scale DER owners could compromise the operator's hierarchical and centralized control to reach system stability and cost optimization. Recent Decentralized Energy Management (DEM) approaches provide flexibility for DERs control, but several existing solutions depend on powerful and expensive computer clusters and their ability to deal with a high burden of data in the communication channel. This work is motivated towards a DEM framework that involves independent DER owners while microgrid operator still maintains a hierarchical control philosophy. The framework must include a method to reduce the need of powerful computer clusters and depend on low bandwidth communications channel. Here, a multi-layered framework for every DER, consisting of physical, control, and agent layers for DEM is approached, where the agent layer participates in the energy management task. An Asynchronous Decentralized PSO (ADPSO) algorithm is proposed for the agent layer based on its primal characteristic: it can reach a consensus state between networked computing units by exchanging asynchronously only the state variable through the communications channel. The proposed solution allows the integration of DEM capabilities within the physical controller of the DERs, distinguishing it from other decentralized solutions. Easiness of implementation and low computational requirements are shown by performing DEM tests on single board computers. The tests show improved convergence rate, improved swarm diversity behavior and fast consensus reaching of DEM optimization.