A multi‐agent privacy‐preserving energy management framework for renewable networked microgrids

This paper proposes a fully distributed scheme to solve the day-ahead optimal power scheduling of networked microgrids in presence different renewable energy resources, such as photovoltaics and wind turbines, considering storage systems. The proposed method enables optimization problem through local computation agents system private communication between existing agents, without any centralized unit. In this paper, cloud-fog-based framework is also introduced fast economical infrastructure for method. suggested optimized an area regulate update policies, detect misbehaving elements, execute punishments centrally, while general manner using eliminates need invest databases computing examined on small-scale microgrid larger test microgrid, including 4 15 areas 24-h time period, illustrate scalability, convergence, accuracy framework. simulation results substantiate precise performance compared with other methods.