Day-ahead real-time pricing strategy based on the price-time-type elasticity of demand

Abstract

The curtailment of the peak demand has great economic and environmental benefits. In this paper, an efficient price profile under the Real-Time Pricing (RTP) option is found out to optimize the regional domestic daily electric load curve. The domestic electric appliances are divided into eight categories, with respect to the difference of their self-price elasticity and crossprice elasticity. In order to set up a reasonable pricing strategy model, both the users' satisfaction and the price are taken into account. The program of RTP is taken and the Particle Swarm Optimization (PSO) algorithm is used to optimize the electricity price profile. Under the optimized price profile, the load curve tends to be more flat and the average price for the customer is lower than before, after the variation and shift of the electric power demand.

The Controller Parameters Optimization for Droop Controlled Distributed Generators in Microgrid

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