The optimal dispatch of a microgrid is of great significance to reduce energy consumption, user’s electricity costs, and environmentalpollution. The microgrid models are not only able to meet the power requirements but also improve the system economically efficient andenvironmentally friendly. In this regard, this paper proposes a new off-grid microgrid model to meet the energy requirement of a small touristicplace in India. This paper proposed a time series analysis of a microgrid that helps to see how the given system’s environmental and economicvariable changes over time. The proposed model optimizes the value of the hybrid power system from utility-scale and distributed generationto standalone microgrid. The paper also discussed the market value of microgrid systems around the globe. The paper used the HOMER gridsoftware simulation tool to analyze the microgrid. It helps to determine the use of the system’s components for demand change reduction whileserving the electric loads. This paper also explains the SARIMA model for forecasting the economical behavior of the microgrid. For the analysisand prediction, only the economic factors are taken into consideration. The analysis compares the performance of the system and shows thatthe system is economically viable concerning the present grid system. To improve the time series analysis information and efficiency of theproposed model, this paper proposes the integration of SARIMA with the HOMER grid software solution. The results show that the effectivenessand superiority of the proposed model. This can reduce the electricity’s costs and pollution of the system.

Electricity demand is rising in lockstep with globalpopulation growth. The present power system, which is almosta century old, faces numerous issues in maintaining a steadysupply of electricity from huge power plants to customers. Tomeet these issues, the electricity industry has enthusiasticallyembraced the new smart grid concept proposed by engineers. Ifwe can provide a secure smart grid, this movement will be moreuseful and sustainable. Machine learning, which is a relativelyrecent era of information technology, has the potential to makesmart grids extremely safe. This paper is a literature survey ofthe application of machine learning in different areas of smartgrids. This paper concludes by mentioning the best machinelearning algorithms that can be used in different aspects of thesmart grid

Electricity demand is rising in lockstep with global population growth. The present power system, which is almost a century old, faces numerous issues in maintaining a steady supply of electricity from huge power plants to customers. To meet these issues, the electricity industry has enthusiastically embraced the new smart grid concept proposed by engineers. If we can provide a secure smart grid, this movement will be more useful and sustainable. Machine learning, which is a relatively recent era of information technology, has the potential to make smart grids extremely safe. This paper is a literature survey of the application of machine learning in different areas of smart grids. This paper concludes by mentioning the best machine learning algorithms that can be used in different aspects of the smart grid.

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Electricity demand is rising in lockstep with global population growth. The present power system, which is almost a century old, faces numerous issues in maintaining a steady supply of electricity from huge power plants to customers. To meet these issues, the electricity industry has enthusiastically embraced the new smart grid concept proposed by engineers. If we can provide a secure smart grid, this movement will be more useful and sustainable. Machine learning, which is a relatively recent era of information technology, has the potential to make smart grids extremely safe. This paper is a literature survey of the application of machine learning in different areas of smartgrids. This paper concludes by mentioning the best machine learning algorithms that can be used in different aspects of the smart grid.