Abstract
Grid computing, utilizing distributed resources, achieves goals in handling workloads in a distributed system. Unlike traditional high-performance computing, grid computing assigns tasks to nodes, showcasing heterogeneity without physical coupling. Grids, with variable sizes based on applications, use general-purpose middleware. In modern energy systems, integrating smart grids and grid computation is vital. Emphasizing resource efficiency, grid computation enhances smart grid performance; by enabling real-time monitoring, rapid adjustments for optimization, and outage prevention. Grid computation supports demand response strategies for electricity management and integrates distributed generation resources, such as solar panels and wind turbines, including autonomous microgrid supervision.
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