Abstract
It has been seen that the power distribution in the networks is becoming more complex and heavily stressed due to the development of decentralized energy resources. In such cases, Demand Side Management (DSM) programs can be utilized in order to maintain the flexibility of the system by alternating the consumption patterns of the customers as well as controlling the loads of the main distribution network. The exploitation of artificial intelligence (AI) methods in DSM applications has been developed in recent years and Particle Swarm Optimization (PSO) is one of the highly accurate methods for resource scheduling and dispatching economically. The research is focused on optimal scheduling of residential loads using the Binary Particle Swarm Optimization (BPSO) algorithm which is the binary version of the widely used PSO algorithm and the aim of this research is to minimize the monthly electricity cost of a typical household based on the Time of Use (TOU) tariff scheme.
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 callDisclaimer: 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.
