Efficient energy consumption system using heuristic renewable demand energy optimization in smart city. (19th October 2020)

• Record Type: Journal Article
• Authors: Shu, Ming; Wu, Shizhong; Wu, Tong; Qiao, Zhonglin; Wang, Nai; Xu, Fei; Shanthini, A.; Muthu, Bala Anand
• Is Part Of: Computational intelligence. Volume 38:Number 3(2022)
• Page Start: 784
• Page End: 800
• Publication Date: 2020-10-19
• Subjects: energy storage system -- IoT -- renewable energy -- smart city; Artificial intelligence -- Periodicals; Computational linguistics -- Periodicals; 006.3
• DOI: 10.1111/coin.12412
• Languages: English
• ISSNs: 0824-7935

Abstract

Abstract: The rapid growth of urban development in recent years required reliable as well as realistic smart solutions to transport, system infrastructure, environmental conditions, and quality of life in smart cities. Furthermore, several innovative and comprehensive applications for smart cities are accessible through the Internet of Things that plays a significant role in reducing the utilization of energy requirements and other environmental effects. Based on the demands in reducing energy consumption, this article designed and developed a combined heat and power design based on the renewable energy system and energy storage system, which helps to minimize the utilization of energy consumption in smart cities. In these concerns, a standardized heuristic renewable demand energy optimization in the smart city (HRDEOSC) architecture is presented, where the smart area domain is distributed into a wide area network. In comparison with the overall domestic energy consumption of electricity and transport, the energy demand for desalination processes is very small and it has been achieved by HRDEOSC. Here, the designed computational model demonstrate that the developed system contributes significantly to our challenges and proved to be an economical approach for the development of the smart structural design which helps to reduce the energy consumption of smart cities.