A review of artificial intelligence-based optimization techniques for the sizing of integrated renewable energy systems in smart cities. Issue 1 (1st January 2020)

• Record Type: Journal Article
• Authors: Kanase-Patil, Amarsingh B.; Kaldate, Avinash P.; Lokhande, Shashikant D.; Panchal, Hitesh; Suresh, M.; Priya, V.
• Is Part Of: Environmental technology reviews. Volume 9:Issue 1(2020)
• Page Start: 111
• Page End: 136
• Publication Date: 2020-01-01
• Subjects: Integrated renewable energy sources (IRES) -- artificial Intelligence -- hybrid renewable energy system (HRES) -- energy management in smart cities; Environmental engineering -- Periodicals; Environmental protection -- Periodicals; 628.05
• DOI: 10.1080/21622515.2020.1836035
• Languages: English
• ISSNs: 2162-2515

Abstract

ABSTRACT: In the Smart City, the Integrated Renewable Energy System (IRES) is playing a crucial role. Integrating the available renewable energy sources is useful in solving energy supply and demand-related issues. For a stable state of energy supply and energy demand, their proper size is needed to adapt to integrated renewable energy sources in the future. To address technical, economic and sizing problems, different algorithms needed to implement the integrated renewable energy scheme, as suggested by various authors. This paper provides a comprehensive review of various topics related to power generation for Smart City based on Integrated Renewable Energy System (IRES). It discusses in detail issues related to the integration of different energy sources, use of smart grids for integration, methods of IRES sizing using software followed by methods of sizing using artificial intelligence algorithms. This article reviews different AI algorithms that focus on the sizing of integrated renewable energy systems in smart cities. GRAPHICAL ABSTRACT: UF0001