Multiple microgrids can operate when interconnected and form a cluster of microgrids, in which each individual system benefits from this cooperation during grid-connected and islanded modes. Therefore, the contents of this paper address the concept of microgrid clusters by providing a review of the literature research conducted towards the project and development of smart grids. Several aspects regarding the operation of microgrid clusters are introduced, including control and energy-management strategies and architecture configurations in terms of layout, power conversion technology and line frequency technology. A brief comparison of these control strategies and architecture configurations is also provided. In the field of electrical protections, most of the electrical protection schemes being proposed in the literature are applied exclusively to individual microgrid systems. Even though only a handful of works and studies focus on the protection of multiple microgrids, this paper contributes a review of electrical protection schemes currently available in the literature for microgrid clusters. In addition, it also addresses energy trading among multiple microgrids and introduces three energy-market designs suitable for implementation in microgrid clusters to facilitate energy trading among the participating prosumers, producers and customers. Finally, a case study is presented to evaluate the cooperation among five industrial microgrids operating in a cluster during islanded mode using an internal market. Each microgrid participating in the network can sell or buy excess energy in order to fulfil its own power requirements. To this end, an algorithm was developed in Matlab, allowing the coordination of the hourly energy trade among these microgrids through three market models with market clearing price/quantity in asymmetric pool.

Renewable and Sustainable Energy Reviews Vol 133
F. Bandeiras, E. Pinheiro, M. Gomes, P. Coelho, J. Fernandes

Link de acesso: 

Review of the cooperation and operation of microgrid clusters – ScienceDirect