Paper Info
Title
Swarm Intelligence Based Home Energy Management Controller Under Dynamic Pricing Scheme.
Abstract
Energy management controller (EMC) is widely adopted for residential load management in smart grid (SG). Its main focus is on minimizing cost with minimal consumer interaction. EMC effectiveness is improved in the context of demand response (DR) program. In the era of demand side management (DSM) EMC plays a significant role in residential energy management by curtailing the peak to average ratio (PAR) and electricity bill. In this research work, we are reducing the electricity cost and PAR by maximizing the user comfort. In our research work, we consider a smart home with three smart appliances and schedule these appliances energy consumption and user comfort by using heuristic techniques: binary particle swarm optimization (BPSO) and firefly algorithm (FA). Simulations are conducted by utilizing the day-ahead real time pricing (DA-RTP). Simulation results depict that firefly algorithm (FA) has better performance as compared to BPSO in term of minimizing cost and PAR, while also maximizing user satisfaction level. A trade-off analysis between user satisfaction and energy consumption cost is demonstrated in simulations.
Year
DOI
Venue
2017
10.1007/978-3-319-69811-3_23
ADVANCES ON BROAD-BAND WIRELESS COMPUTING, COMMUNICATION AND APPLICATIONS, BWCCA-2017
Field
DocType
Volume
Load management,Energy management,Mathematical optimization,Smart grid,Computer science,Dynamic pricing,Demand response,Firefly algorithm,Home automation,Energy consumption
Conference
12
ISSN
Citations 
PageRank 
2367-4512
0
0.34
References 
Authors
7
7
Name
Order
Citations
PageRank
Adnan Ahmed1618.92
Muhammad Hassan Rahim2206.11
Fozia Feroze301.35
Ayesha Zafar4131.78
Itrat Fatima513.75
Sheraz Aslam601.01
Nadeem Javaid71043222.46