Scheduling Operations of Smart Appliances Using Demand Response

Abstract

Nowadays, many countries are concerned about the environmental problems which are mainly caused due to insensible and careless use of energy. The ignorance of the people towards energy consumption is greatly affecting the environment. The contribution of electric sector in polluting the environment is the highest among all other sectors that work on energy. High demands of electricity during peak hours result in increased production of electricity using fossil fuel based plants which increases the level of CO2 in the atmosphere. However improved performance of the grid system in reducing the peak loads and availability of electricity can reduce the green house gas emission which is considered as the main reason of climate change. The work in this chapter is mainly focused on optimal load scheduling for energy cost minimization and peak load reduction. The proposed model uses Time of Use (TOU) pricing tariff in the optimization process. The optimization problem has been solved with multiple optimization techniques including Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and a hybrid algorithm formed by combining GA and PSO. The proposed scheme has many applications like peak load reduction and energy cost minimization which can benefit consumers and utilities.