Harnessing AI and IoT for Optimized Renewable Energy Integration and Resource Conservation

Abstract

This paper reviews various methods of integration of AI and IoT technologies in renewable energy (RE) systems. The reason of the integration is to optimise the energy production, distribution and consumption. With this current reported work, we intended to study many AI applications, including machine learning (ML) and Deep Learning (DL). The work also highlights the potential techniques to enhance the efficacy, reliability and sustainably of RE energy sources. The various challenges associated with this integration are also studied here. This work analyses the current research and industry trends, which further is useful in providing insights in the AI driven future for RE energy solutions. The RE sources that are focused here are solar, wind and its energy management. Integration of AI into this domain will enhance the modelling and other process such as RE generation, grid management and distribution of energy. Further, it is noticed that the integration of IoT will help in optimising the consumption of energy which is the need of the hour. This will lead in the reduction of electricity bills in household and commercial places. Additionally, when AI and IoT are used in conjunction, the resilience of power systems us enhanced.