TY - GEN
T1 - An optimal differential pricing in smart grid based on customer segmentation
AU - Meng, Fanlin
AU - Kazemtabrizi, Behzad
AU - Zeng, Xiao Jun
AU - Dent, Chris
N1 - Funding Information:
ACKNOWLEDGMENT This work was partly supported the Engineering and Physical Sciences Research Council, UK (Grant No. EP/K002252/1). The first author would like to thank Durham Energy Institute for the DEI Small Grant funding.
Publisher Copyright:
© 2017 IEEE.
PY - 2018/1/18
Y1 - 2018/1/18
N2 - 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.
AB - 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.
KW - customer segmentation
KW - demand response
KW - Differential pricing
KW - smart metering data
UR - http://www.scopus.com/inward/record.url?scp=85046281697&partnerID=8YFLogxK
U2 - 10.1109/ISGTEurope.2017.8260255
DO - 10.1109/ISGTEurope.2017.8260255
M3 - Conference contribution
AN - SCOPUS:85046281697
T3 - 2017 IEEE PES Innovative Smart Grid Technologies, Europe
SP - 1
EP - 6
BT - 2017 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe)
PB - IEEE
CY - New Jersey
T2 - 2017 IEEE PES Innovative Smart Grid Technologies Conference Europe, ISGT-Europe 2017
Y2 - 26 September 2017 through 29 September 2017
ER -