Demand Side Management Using Particle Swarm Optimization

The conventional grid only permits one-way information and power flow due to its usage of solid-state and electromechanical technologies, but renewable energy sources are introduced nowadays, so two-way flow of electricity is achieved with the help of smart grid. Demand side management is currently gaining popularity in the smart grid due to its many benefits for electricity cost and dependable performance. All participants in a ladder-like day-to-day smart grid model, including customers, the demand response aggregator, and the utility, want to boost their profits. The problem of load shifting has been approached hour by hour, starting in the morning and concluding in the last hour of the day, in an effort to minimize peak demand and save electricity costs, calculate the peak demand and controllable load and controllable load is moved to the off-peak time to reduce the peak demand in benefit of utility, and offer good rates per unit to encourage customer to change their usage. With the conventional method only single solution is achieved, so for the multi-solution AI is required. In order to achieve load shifting through minimization of the problem, the particle swarm optimization (PSO) approach has been utilized in three smart grid region loads for the DSM problem: industrial, commercial, and residential.