Artificial intelligence on economic evaluation of energy efficiency and renewable energy technologies. (October 2021)

• Record Type: Journal Article
• Authors: Chen, Cheng; Hu, Yuhan; Karuppiah, Marimuthu; Kumar, Priyan Malarvizhi
• Is Part Of: Sustainable energy technologies and assessments. Volume 47(2021)
• Publication Date: 2021-10
• Subjects: Artificial intelligence -- Economic evaluation -- Energy efficiency -- Renewable energy; Renewable energy sources -- Periodicals; Energy development -- Technological innovations -- Periodicals; Electric power production -- Periodicals; Energy storage -- Periodicals; 333.79
• DOI: 10.1016/j.seta.2021.101358
• Languages: English
• ISSNs: 2213-1388

Abstract

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.