Title: Hybrid genetic-annealing algorithm for intelligent power consumption of a large building

Authors: Yanping Li; Boying Shi; Tao Wang; Linyan Wu; Qi Wang

Addresses: School of Information and Electrical Engineering, Shandong Jianzhu University, Ji'nan 250100, China ' School of Information and Electrical Engineering, Shandong Jianzhu University, Ji'nan 250100, China ' School of Information and Electrical Engineering, Shandong Jianzhu University, Ji'nan 250100, China ' School of Information and Electrical Engineering, Shandong Jianzhu University, Ji'nan 250100, China ' School of Information and Electrical Engineering, Shandong Jianzhu University, Ji'nan 250100, China

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.

Keywords: architectural smart power; hybrid genetic-annealing algorithm; indoor comfort.

DOI: 10.1504/IJICA.2018.092595

International Journal of Innovative Computing and Applications, 2018 Vol.9 No.2, pp.90 - 97

Received: 22 Nov 2017
Accepted: 10 Feb 2018
Published online: 25 Jun 2018 *

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