A Particle Swarm Optimization and Branch and Bound Based Algorithm For Economical Smart Home Scheduling

被引：0
|
作者：
Wang, Yangyizhou [1 ,2 ]
Hao, Cong [1 ]
Yoshimura, Takeshi [1 ]
机构：
[1] Waseda Univ, Grad Sch IPS, Hibikino 2-7, Kitakyushu, Fukuoka 8080135, Japan
[2] Shanghai Jiao Tong Univ, 800 Dongchuan Rd, Shanghai 200240, Peoples R China
来源：
2017 IEEE 60TH INTERNATIONAL MIDWEST SYMPOSIUM ON CIRCUITS AND SYSTEMS (MWSCAS) | 2017年
关键词：
Smart Home Scheduling; Particle Swarm Optimization; Branch and Bound;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
Smart home scheduling, as one of the most effective techniques in Demand Side Management (DSM), is now attracting more and more research interests in the recent years. In this paper we propose an efficient scheduling algorithm for smart home resident to reduce the monetary cost of the electricity. The proposed algorithm is an improved particle swarm optimization(PSO) algorithm that can schedule the smart appliances under discrete power level and quadratic pricing model. Branch and bound method is adopted to map real number values to discrete power level values. Simulation results shows that our method exceeds the previous methods both in total monetary cost and execution time.
引用
收藏
页码：213 / 216
页数：4
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