Abstract

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.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.