Energy management system using binary particle swarm optimization technique.

In this modern world, human life has become increasingly reliant on electricity, which serves to be one of the basic needs of human to lead a normal life. As the usage of electricity has increased over the years, the consumers are very much concerned about its consumption rate and the electricity bill generated out of it. Hence monitoring the consumption rate stands first which is very trivial and challenging by designing an efficient energy management system. This paper outlines the survey on energy management systems implemented with artificial intelligence techniques towards finding a viable solution to the aforementioned issue. This study elucidates how artificial intelligent systems are incorporated in different energy management systems to match demand and supply. A comparative analysis of different intelligent techniques with optimization goals, issues and solutions, applied to the energy management systems for effective functioning is also presented. Finally, Home Energy Management System (HEMS) using Binary Particle Swarm Optimization Algorithm (BPSO) is presented. 26% reduction in the daily bill with optimization of HVAC and non-interruptible appliances was attained. Due to the interrupted supply of energy sources, effective storage model is determined to be an alternate viable option owing to technological advancement and capacity of ensuring excellent grid services. Future directions in terms of developing hybrid systems using hybrid energy sources and intelligent systems are also suggested. [ABSTRACT FROM AUTHOR]