An optimal differential pricing in smart grid based on customer segmentation

Fanlin Meng, B. Kazemtabrizi, Xiao-Jun Zeng, C. Dent
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引用次数: 4

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.
基于客户细分的智能电网最优差异定价
在智能电网中,动态定价(如分时电价(ToU)、实时电价(RTP))最近引起了学术界和工业界的极大兴趣。尽管差别定价已被广泛应用于零售行业,如宽带和移动电话服务,为“合适的”客户提供“合适的价格”,但现有的智能电网零售定价研究主要集中在统一的动态定价(即所有客户都以相同的价格提供)。在本文中,我们对基于客户细分的智能电网零售定价的最优差异定价迈出了第一步。首先提出了一个差别定价框架,该框架包括顾客细分分析和零售商与每个顾客群体之间的两级最优差别定价问题。在上层,为零售商制定定价优化问题,而在下层,为每个客户群(例如,价格敏感型,价格不敏感型)制定最优费率选择问题,以最小化其账单。通过与基准统一分时电价的比较,仿真结果证实了本文提出的最优差异定价策略的可行性和有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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