Optimal Scheduling of Customers' Demand based upon Power Availability and its Price in Smart Grid

This study concentrates on modeling of customer load scheduling of delayable and non-delayable appliances. Considering a group of 20 customers with a Distribution Channel (DC) acts as an Aggregator, which are willing to participate in Demand response (DR) and in Energy Market (EM). Firstly, each customer load scheduling of appliances is done with Delayable Appliances and Non-Delayable Appliances using forecasted Day-Ahead Price, where Non-Delayable Appliance can reduce their power and Delayable Appliances can delay their operation time with in the time period limit set by the customer in a day. The cumulative load information goes to Distribution channel which re-adjusts again only Delayable Appliances. Distribution Channel adjustment is divided into two cases, viz., first with respect to available power and, second with respect to the price of power at that time. Some customers are having solar PV as a generation with battery storage. The scheduling of appliances is assumed as an optimization problem and solved through Genetic Algorithm Optimization (GAO). The results from Day-ahead and Hour-ahead scheduling can help in matching closely load for real-time consumption. This method has social benefits, which benefits the customer as well as utility.