Optimal bidding strategy of a retail electric provider in a smart grid environment

A retail electric provider (REP) can provide incentives to its customers by providing real-time prices (RTPs) to regulate their consumption based on announced prices. The economic viability and the profitability of the retailer are highly dependent on how to design RTPs according to the feedback between the generation utilities and the consumption pattern of consumers. The presence of two-way flow of power and information in the smart grid concept can lead to improvement of the network operation. In this paper, the optimal bidding strategy of a REP in the smart grid environment is studied. Stackelberg game theory is utilized for modeling the interaction between REP and customers. Also, the various RTPs is offered to the customers depending on their load profile. A new method, called demand pattern extraction (DPE), is used for clustering the customers. The proposed model is applied on a realistic case study, and the optimal design of RTPs are investigated.