Artificial intelligence on economic evaluation of energy efficiency and renewable energy technologies. (October 2021) - Chen, Cheng; Hu, Yuhan; Karuppiah, Marimuthu; Kumar, Priyan Malarvizhi
Abstract: The energy sector currently faces growing challenges related to increasing demand, efficiency, a lack of analytics required for optimal management, and changing supply and demand patterns. Renewable energy technologies such as Energy forecasting, energy efficiency, and energy accessibility are the key factors that incorporate Artificial intelligence. In this paper, the Artificial Intelligence-based useful evaluation model (AIEM) has been proposed for forecasting renewable energy and energy efficiency impact on the economy. This study intended to analyze, compare and build a model utilizing artificial intelligence and specific economic indicators significant in economic prediction regarding renewable energy. AI approaches that can be employed to overcome different challenges, including selecting the best consumer to react for the attributes and desires, competitive pricing, scheduling, and managing facilities, incentivizing demand response participants, and compensating them equally and economically. The proposed model can help enhance energy efficiency to 97.32% and improve renewable energy resource utilization.