Cookies

We use cookies to ensure that we give you the best experience on our website. You can change your cookie settings at any time. Otherwise, we'll assume you're OK to continue.

Durham University

Research & business

View Profile

Publication details

Meng, F., Kazemtabrizi, B., Zeng, X. J. & Dent, C. (2017), An Optimal Differential Pricing in Smart Grid Based on Customer Segmentation, ISGT Europe 2017. Torino, Italy, IEEE, Piscataway, 1-6.

Author(s) from Durham

Abstract

In smart grids, dynamic pricing (e.g., time-of-use pricing (ToU), real-time pricing (RTP)) has recently attracted enormous interests from both academia and industry. Although differential pricing has been widely used in retail sectors such as broadband and mobile phone services to offer ‘right prices’ to ‘right’ customers, existing research in smart grid retail pricing mainly focus on an uniform dynamic pricing (i.e. all customers are offered at the same prices). In this paper, we take the first step towards an optimal differential pricing for smart grid retail pricing based on customer segmentation. A differential pricing framework is firstly presented which consists of customer segmentation analysis, and a two-level optimal differential pricing problem between the retailer and each customer group. At the upper level, a pricing optimization problem is formulated for the retailer while at the lower-level, an optimal tariff selection problem is formulated for each customer group (e.g., price sensitive, price insensitive) to minimize their bills. By comparing with a benchmarked uniform ToU, simulation results confirmed the feasibility and effectiveness of our proposed optimal differential pricing strategy.