An Ml System Helps Smart Grids Manage the Amount of Power Electric Vehicles Draw

Jaymin Pareshkumar Shah

doi:10.70528/IJLRP.v5.i8.1468

An Ml System Helps Smart Grids Manage the Amount of Power Electric Vehicles Draw

Author(s)	Jaymin Pareshkumar Shah
Country	India
Abstract	Real-time electric vehicle power consumption optimization within smart grids relies on machine learning systems as the main subject of this research paper. The rapid growth of electric vehicle adoption creates essential challenges to power grid stability and efficiency because of rising electricity demands. ML algorithms within SM networks can enable real-time observations and commanding EV loading behaviors to meet the peak and incentive conditions. The research examines multiple ML strategies, such as supervised learning, reinforcement learning, and clustering algorithms, which study EV charging patterns to predict grid operational effects. Predictive models must be developed according to research because they require historical usage data along with user behavior information and real-time grid conditions for accurate EV charging need assessment. By exploiting these models, utilities can execute demand-response techniques that optimize charging schedules, alleviate peak load stress, and strengthen the grid, strengthening and correcting the network and giving the additional want that the load requests, not applying tension on the utility, in order to that it makes a profit and meets needs at a reduced cost. The paper examines how the Internet of Things devices serve as communication tools for allowing data interactions between electric vehicles, charging stations, and grid operators to achieve more substantial power management flexibility. The findings demonstrate that machine learning systems are an effective solution for smart grids to improve electrical vehicle power management procedures. With the help of advanced analytics and predictive analytics, utility companies better improve their operational profitability and contribute to the broader transition of pollution-free transportation solutions. This research establishes essential knowledge for future investigations about ML-based smart grid infrastructure integration, which drives better energy management capabilities in expanding electric transport systems.
Field	Engineering
Published In	Volume 5, Issue 8, August 2024
Published On	2024-08-09
Cite This	An Ml System Helps Smart Grids Manage the Amount of Power Electric Vehicles Draw - Jaymin Pareshkumar Shah - IJLRP Volume 5, Issue 8, August 2024. DOI 10.70528/IJLRP.v5.i8.1468
DOI	https://doi.org/10.70528/IJLRP.v5.i8.1468
Short DOI	https://doi.org/g898vv

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An Ml System Helps Smart Grids Manage the Amount of Power Electric Vehicles Draw

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