Real-time retail price determination in smart grid from real-time load profiles

In a vertical organizational structure, component of a particular level has predetermined line of control from the objects of the management layer above it, but in horizontal organizational structure, objects of a layer are free to select the objects above them. The smart grid has a horizontal organizational structure compared to the power grid with vertical organization structure. This change in organizational structure always enabled independent operation of the components and demanding efficiency and profitability from these components. The distribution system of smart grid with a number of retailers in the market is relying on real-time pricing to minimize the burden on consumers and to maximize its profit. In real-time pricing, consumers are segmented based on their usage pattern and charged accordingly. In this paper, we formulated this complicated optimization problem and succeeded in computing real-time selling prices for the consumers. For accurate and secure clustering, a new method is used, which is also well suitable for a big data environment like the smart grid. Consideration of price elasticity of consumers along with load profile, in the real-time selling price determination, is the novelty of our paper. The optimization problem of profit maximization for retailers is solved using real-time metering data collected from consumers in a smart grid pilot project in India. The results clearly show that real-time prices for each class of consumers are according to their load profile.