Real-time Pricing with Consumers Estimation by a Particle Filter

Abstract

We propose a novel real-time pricing method for an electric power system based on model predictive control by the real-time optimization and estimation of a consumer's parameter using a particle filter. We also modify an existing control scheme for a thermal power plant and a battery to supplement price presentation. We conducted numerical simulations to compare the performance of our proposed method with that of the direct control scheme used in the previous research. We demonstrate that a supply-demand balance is achieved by price presentation in spite of a large fluctuation in wind power and the uncertainty in a consumer's parameter.