Multi Objective Flexible Load Scheduling in Smart Home Based on Grey Wolf Algorithm

Authors

Bao Yi, 1. Hangzhou Telek Technology Co., Ltd., Hangzhou 310012, China;;
Dai Bo, 2. State Grid Corporation of China at Hangzhou, Hangzhou 310007, China;;
Zhihua Wang, 1. Hangzhou Telek Technology Co., Ltd., Hangzhou 310012, China;;
Wanliang Wang, 3. Computer Science & Technology, Zhejiang University of Technology, Hangzhou 310014, China;

Abstract

Abstract: A three level electricity price model is designed based on the electricity consumption. A comfort model of multi parameters is designed for optimizing the grid load control of temperature and the humidity, light intensity and human activity. Grey wolf algorithm is used to solve the multi-objective problem. The grey wolf algorithm has its superiority in solving high dimensional and multi peak of complex function problems. Theoretical and experimental analysis shows that the grey wolf algorithm in accuracy and stability is better than particle swarm optimization algorithm and differential evolution algorithm. The simulation results show that the proposed algorithm can make user comfort and reduce the power consumption.

Recommended Citation

Yi, Bao; Bo, Dai; Wang, Zhihua; and Wang, Wanliang (2019) "Multi Objective Flexible Load Scheduling in Smart Home Based on Grey Wolf Algorithm," Journal of System Simulation: Vol. 31: Iss. 6, Article 23.
DOI: 10.16182/j.issn1004731x.joss.17-0188
Available at: https://dc-china-simulation.researchcommons.org/journal/vol31/iss6/23

First Page

1216

Revised Date

2017-07-10

DOI Link

https://doi.org/10.16182/j.issn1004731x.joss.17-0188

Last Page

1222

CLC

TP3-0

Recommended Citation

Bao Yi, Dai Bo, Wang Zhihua, Wang Wanliang. Multi Objective Flexible Load Scheduling in Smart Home Based on Grey Wolf Algorithm[J]. Journal of System Simulation, 2019, 31(6): 1216-1222.

DOI

10.16182/j.issn1004731x.joss.17-0188