Total Optimization of Smart Community by Differential Evolutionary Particle Swarm Optimization. Issue 1 (July 2017)

• Record Type: Journal Article
• Authors: Sato, Mayuko; Fukuyama, Yoshikazu
• Is Part Of: IFAC-PapersOnLine. Volume 50:Issue 1(2017)
• Page Start: 201
• Page End: 206
• Publication Date: 2017-07
• Subjects: Energy management systems -- Optimization problems -- Heuristic searches -- Renewable energy system -- Energy storage -- Gas turbines -- Boilers; Automatic control -- Periodicals; 629.805
• DOI: 10.1016/j.ifacol.2017.08.034
• Languages: English
• ISSNs: 2405-8963

Abstract

Abstract: This paper proposes a total optimization method of a smart community (SC) by Differential evolutionary particle swarm optimization (DEEPSO). Various sectors of SC models such as an electric utility model, an industry model, and a building model are utilized in this paper. Whole of a SC is optimized in order to minimize energy costs, shift electric power load peak at high load hours, and minimize total CO2 emission of the SC using the models. The simulation results by the proposed method are compared with those by Particle swarm optimization (PSO), Differential Evolution (DE), and Evolutionary particle swarm optimization (EPSO) based methods.