Real -Time Demand Response Control for Smart Grid based on User Preference

Abstract

The promising solution to the future energy crisis will be smart grids. One of the smart grid's most important features is its active Demand Response (DR) model that allows consumers to shape their daily energy consumption patterns so that they can reduce their energy use and peak to average ratio (PAR). A bidirectional structure for interaction between end users and service providers has been suggested. They favor the user-based scheduling approach of energy consumption, which allows consumers to use electricity smartly. A real-time pricing scenario is being implemented which allows consumers to reshape their demand profile within hours of low prices. To prevent grid overloading during load shifting, during each time slot, we set the maximum power limit for the residential unit. The approach aims to schedule the devices according to their needs, thereby maximizing the use of power and reducing the cost of use. The problem of optimization for the scheduling of consumption was solved using genetic algorithms.