Personalized pricing: A new approach for dynamic pricing in the smart grid

Among many key subjects in the smart grid technology, Demand Side Management (DSM) which is one of the common and popular subjects interests researchers on controlling and monitoring customers' consumption activities. In reality, DSM involves any activities that impress customer's consumption levels in a power grid system. This usually happens by means of employing new policies by utility companies, defining suitable pricing schemes that guarantee grid's continual working and using effective scheduling approaches to adjust hourly customer's consumption levels, especially on peak-time hours. Among them, pricing methods are very important and effective in controlling customer's consumption patterns. Real-Time Pricing (RTP) and Time of Use (TOU) pricing are common approaches which are being employed by many utility companies and are mostly dependent on the grid's dynamic load behavior. In addition, real-time pricing methods adjust real-time prices based on grid's real-time demand level dynamically. In this paper, we propose a new pricing method that not only makes use of grid's real-time consumption data but also considers consumption levels of each customer and define real-time prices individually (Personalized Pricing). This means that the consumption price for each individual customer will be adjusted by the changes that occur during the course of power consumption and also reflect each individual customer's habit of using electricity. In this way, our proposed method can consider both grid and individual customer's consumption level to adjust real-time prices. Generally personalized pricing is a type of an incentive-based DSM model that can impress customer's consumption levels by persuading them to decrease their consumption levels during peak-time hours and updating each customer's consumption prices individually. However, individual satisfaction is a more important capability that lies at the heart of Personalized Pricing. Our results also intensify that most of our customers in the grid will decrease their consumption levels during peak-time hours to reduce their electricity consumption costs.