Hybrid genetic-annealing algorithm for intelligent power consumption of a large building. (2018)

• Record Type: Journal Article
• Authors: Li, Yanping; Shi, Boying; Wang, Tao; Wu, Linyan; Wang, Qi
• Is Part Of: International journal of innovative computing and applications. Volume 9:Number 2(2018)
• Page Start: 90
• Page End: 97
• Publication Date: 2018
• Subjects: architectural smart power -- hybrid genetic-annealing algorithm -- indoor comfort; Evolutionary computation -- Periodicals; Neural networks (Computer science) -- Periodicals; Genetic programming (Computer science) -- Periodicals; Biologically-inspired computing -- Periodicals; Swarm intelligence -- Periodicals; Quantum computers -- Periodicals; 006.3
• Languages: English
• ISSNs: 1751-648X

Abstract

At present, the electrical equipment in buildings is constantly increasing, and correspondingly, the energy consumption is also greatly improved. Therefore, scientific and intelligent power consumption is particularly important. In this paper, the main factors that affect the room environment are modelled, such as room temperature, and light intensity. At the same time, genetic annealing algorithm is introduced to solve the multi-objective optimisation of the parameters of the electrical equipment, find the best strategy for intelligent power system. Finally, the simulation is carried out on the MATLAB platform, and the simulation results show that it has good energy saving effect of architectural smart power system.