Demand response modelling and analysis in smart grid

Abstract

In recent years, the increase in power demand by various infrastructural development activities and industrial automation have affected the load demand. To effectively manage the load demand in a smart grid, several Load Management (LM) techniques have been adopted in making energy policy decisions. In the deregulated power system, the Demand Side Management (DSM), owing to its advantages in economic environments, is regarded as a remarkable choice and has been extended to incorporate Demand Response Programs (DRPs) in the load management techniques. In the implementation of the Demand Response (DR) in the smart grid, various challenges need to be addressed namely, motivating the consumers to take part in the DR scheme in a secure environment, technology up-gradation for utilizing smart appliances, prediction of the power usage of the consumer through behavior analytics. Hence, this research focuses on a novel solution to motivate the consumer to participate in DSM and application of DR. newline newlineIn this research, three functionalities are formulated such as, game theory based DSM with single and multi-utility, demand response management through load forecasting, and applying DR for unit commitment and congestion management problems. newline newlineThe game theory based DR model is to develop an energy scheduler using a game theory algorithm that provides different optimum pricing schemes for each consumer under the utility provider. The algorithm depends on each consumer s decision with his own winning strategy and secondarily on all other consumers individual decisions. newline