Automated Scheduling And Optimization Of Load In Smart Grid Solution For Charging And Discharging Using Artificial Neural Network

Abstract

A smart grid is defined as the combination of automation and communication that can monitor the system. It includes the two way communication network with digital communication technology. Customer participation by actively reducing or shifting the loads from peak hours to nonpeak hours with respect to the pricing scheme is done by DR schemes. So the necessity of developing new approaches for Demand response in smart grid is very important considering all the aspects of the utility provider and the consumers. This dissertation aims to gain an outlook of demand side response modelling in smart grid scenario mainly focusing on residential consumers using different intelligent approaches and strategies. The two key fact of the model are maximizing the utility profit and
minimizing the cost of the user considering the users comfort. DR modelling is done using genetic algorithm considering the important feature of DR congestion. New controller design with residential appliances for DR modeling is executed. The entire work proposes demand response models for residential consumers is done with a real time implementation