Paper Info
Title
Home Energy Management In Smart Grid Using Evolutionary Algorithms
Abstract
Home Energy Management Systems (HEMS) have been widely used for energy management in smart homes. Energy management in a smart home is a challenging task, which require efficient scheduling of appliances. The main focus of HEMS is to schedule the operation of appliances in such a way that it gives us optimized performance in terms of Peak to Average Ratio (PAR), Electric Cost (EC) minimization, execution time and User Comfort (UC). The Time of Use (ToU) pricing scheme is used in this paper. We used Genetic Algorithm (GA), Biogeography-based optimization (BBO) and our proposed hybrid Genetic Biogeography-based Optimization (GBBO), techniques to schedule appliances in single home and for multiple homes. Simulations are carried out using eight different appliances. The results show that GA and GBBO execute better in case of PAR reduction and EC minimization. GBBO outperforms in terms of user comfort. We calculated the UC in terms of waiting time.
Year
DOI
Venue
2018
10.1109/AINA.2018.00154
PROCEEDINGS 2018 IEEE 32ND INTERNATIONAL CONFERENCE ON ADVANCED INFORMATION NETWORKING AND APPLICATIONS (AINA)
Keywords
Field
DocType
smart grid, demand response, appliance scheduling, genetic algorithm, peak-to-average ratio, user comfort
Energy management,Evolutionary algorithm,Smart grid,Scheduling (computing),Computer science,Home automation,Minification,Execution time,Genetic algorithm,Distributed computing
Conference
ISSN
Citations 
PageRank 
1550-445X
0
0.34
References 
Authors
0
7
Name
Order
Citations
PageRank
Abdul Saboor100.68
Nadeem Javaid21043222.46
Zafar Iqbal36517.87
Zaheer Abbas401.01
Ahmad Jaffar Khan500.68
Saad Rashid600.68
Muhammad Awais717951.40