Abstract
Abstract: The smart energy management system was developed with the ability to record, store, and process power consumption data for all major home and industrial devices. Artificial intelligence technologies such as decision making and XG Boost have made advances in power electronics and energy engineering. These technologies provide powerful tools for designing, simulating, controlling, estimating, and fault diagnostic control of modern smart grids and renewable energy systems. AI technology has evolved rapidly over the past few decades, and its applications in modern industrial systems are growing rapidly. Power consumption data can be accessed from the web portal and handheld devices. Homeowners and industry companies can track power consumption by appliance, device, facility, or device. This allows you to better adjust your power consumption. Using the weather forecast, the system decides to switch between photovoltaics or grids using a machine learning concept-based deterministic algorithm. Keywords: Control of smart grid, Energy management system, Artificial Intelligence, Machine Learning, Decision making
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