Demand Response based Automatic Generation Control in smart-grid deregulated market

Abstract

Demand response is a dynamic mechanism which helps to manage customer participation in response to power supply conditions under smart grid environment thereby contributing in system operation studies like Automatic Generation Control. This paper, which consists of two parts, presents Automatic Generation Control scheme under a deregulated environment using demand response. The first part proposes a transfer function model for power gain that can be achieved from price based demand response of thermostatically controlled loads. The second part proposes an Automatic Generation Control scheme under a deregulated system involving competing generation companies. In this paper Automatic Generation Control has been modeled as a collaborative stochastic game using Reinforcement based Learning. The advantage of this model is that the generation companies produce optimal amount of power that is required to minimize their cost of power production, while preserving the spirit of deregulation. Reinforcement Learning based Automatic Generation Control scheme incorporating demand response transfer function was simulated. The simulation results show that this approach can minimize the frequency deviation during load frequency control. The main contribution of the paper is the proposal of an AGC scheme that is suitable under smart grid (Demand Response) and deregulated environment (Competition among Generation companies).