ABSTRACT
Current days, large-scale buildings are the major energy consumers in the world. In most of the cases, energy is wasted than using effectively in buildings. Clients always request optimum energy consumption levels when new buildings are designed. In a conventional elevator system, the regenerative energy is dissipated as heat in a set of resistors when braking occurs. The main modification to be done for the motor drive to collect this energy is to replace the passive rectifier in the drive input side with an active AC/DC converter. Traditionally, these converters are controlled with proportional–integral controllers. Modern experiments reveal that this type of arrangements has some restrictions in practical applications. This research explores on mitigating such limitations by applying a neural network (NN) in regulating active front end converters in such systems. Further, it proposes an NN-related switching regulation scheme for bi-directional AC/DC converters, improving the efficiency of extracting regenerative energy in elevator systems.
