Mbungu, Nsilulu TresorIsmail, Ali A.AlShabi, MohammadBansal, Ramesh C.Elnady, A.Hamid, Abdul Kadir2023-07-242023-07-242023-06Mbungu, N.T., Ismail, A.A., AlShabi, M. et al. 2023, 'Control and estimation techniques applied to smart microgrids : a review', Renewable and Sustainable Energy Reviews, vol. 179, art. 113251, pp. 1-21, doi : 10.1016/j.rser.2023.113251.1364-0321 (print)1879-0690 (online)10.1016/j.rser.2023.113251http://hdl.handle.net/2263/91602DATA AVAILABILITY : No data was used for the research described in the article.The performance of microgrid operation requires hierarchical control and estimation schemes that coordinate and monitor the system dynamics within the expected manipulated and control variables. Smart grid technologies possess innovative tools and frameworks to model the dynamic behaviour of microgrids regardless of their types, structures, etc. Various control and estimation technologies are reviewed for developing dynamic models of smart microgrids. The hierarchical system of a microgrid control consists of three architectural layers, primary, secondary and tertiary, which need to be supported by real-time monitoring and measurement environment of the system variables and parameters. Various control and estimation schemes have been devised to handle the dynamic performance of microgrids in the function of control layers requirement. Firstly, control schemes in the innovative grid environment are evaluated to understand the dynamics of the developed technologies. Six control technologies, linear, non-linear, robust, predictive, intelligent and adaptive, are mainly used to model the control design within the layer(s) regardless of the types of microgrids. Secondly, the estimation technologies are evaluated based on the state of variables, locations and modelling of microgrids that can efficiently support the performance of the controllers and operating microgrids. Finally, a future vision for designing hierarchical and architectural control techniques for the optimal operation of intelligent microgrids is also provided. Therefore, this study will serve as a fundamental conceptual framework to select a perfect optimal design modelling strategy and policy-making decisions to control, monitor and protect the innovative electrical network.en© 2022 Elsevier Ltd. All rights reserved. Notice : this is the author’s version of a work that was submitted for publication in Renewable and Sustainable Energy Reviews. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms are not reflected in this document. A definitive version was subsequently published in Renewable and Sustainable Energy Reviews, vol. 179, art. 113251, pp. 1-21, doi : 10.1016/j.rser.2023.113251.Control designDigitisationDistributed energy generationDistributed energy systemEnergy storage systemOptimal controlRenewable energy systemSmart gridsState estimationSDG-07: Affordable and clean energyPreprint Article