Analysis of energy management schemes for renewable-energy-based smart homes against the backdrop of COVID-19. (August 2022)

• Record Type: Journal Article
• Authors: Ayub, Sara; Ayob, Shahrin Md; Tan, Chee Wei; Taimoor, Muhammad; Ayub, Lubna; Bukar, Abba Lawan; Daud, M.Z.
• Is Part Of: Sustainable energy technologies and assessments. Volume 52:Part B(2022)
• Publication Date: 2022-08
• Subjects: Smart Home Energy Management Systems -- COVID 19 -- Renewable energy resources -- Smart grid -- Demand side management; Renewable energy sources -- Periodicals; Energy development -- Technological innovations -- Periodicals; Electric power production -- Periodicals; Energy storage -- Periodicals; 333.79
• DOI: 10.1016/j.seta.2022.102136
• Languages: English
• ISSNs: 2213-1388

Abstract

Abstract: This article reviews energy management schemes for smart homes integrated with renewable energy resources in the context of the COVID-19 pandemic. The incorporation of distributed renewable energy system has initiated an acute transition from the traditional centralized energy management system to independent demand responsive energy systems. Renewable energy-based Smart Home Energy Management Systems (SHEMSs) play a vital role in the residential sector with the increased and dynamic electricity demand during the COVID-19 pandemic to enhance the efficacy, sustainability, economical benefits, and energy conservation for a distribution system. In this regard, the reviews of various energy management schemes for smart homes appliances and associated challenges has been presented. Different energy scheduling controller techniques have also been analyzed and compared in the COVID-19 framework by reviewing several cases from the literature. The utilization and benefits of renewable-based SHEMS have also been discussed. In addition, both micro and macro-level socio-economic implications of COVID-19 on SHEMSs are discussed. A conclusion has been drawn given the strengths and limitations of different energy scheduling controllers and optimization techniques in the context of the COVID-19 pandemic. It is observed that renewable-energy-based SHEMS with improved multi-objective meta-heuristic optimization algorithms employing artificial intelligence are better suited to deal with the dynamic residential energy demand in the pandemic. It is hoped that this review, as a fundamental platform, will facilitate the researchers aiming to investigate the performance of energy management and demand response schemes for further improvement, especially during the pandemic.