Cost Minimization in a Smart Grid using a Genetic Algorithm

Abstract

Demand side management (DSM), which intelligently manages loads, will be a key component of the smart grid of the future. DSM initiatives provide several advantages when implemented through smart city home energy management systems. Utilities operate at lower peak demand, and consumers benefit from lower electricity prices. This research presents a genetic algorithm based DSM model for residential customers' appliance scheduling. The following scenario—smart houses using renewable energy sources—is simulated in the time-of-use pricing environment of the model. According to simulation findings, the suggested approach schedules the appliances in an ideal way, which lowers power bills.