• Grid computing frameworks are framed as scalable, cross-domain infrastructure for smart grids, enabling distributed resource sharing, middleware, and global collaboration across energy and computation domains [1], [2], [4], [5], [7], [10].

• Research converges on integrating distributed energy resources (fuel cells, PV, wind) and microgrids with grid control, focusing on dynamic models, converter control, and stability implications for grid-connected operation [6], [9], [11], [12], [14], [18].

• A recurring safety pattern evaluates islanding prevention and protective relaying for grid-connected PV, contrasting standards with practical reliability concerns to prevent unintended island behavior [3], [8].

• Monitoring and performance analysis emerge as core methods, with architectures and toolkits for grid resource management and analysis (GridRM, CrossGrid, SCALEA-G) enabling real-time insight into grid operation [10], [13], [19], [20].

• Economic-oriented resource management explores architectures for optimizing global computational grids and distributed energy storage integration, highlighting energy economy and management in grided systems [15], [17].