Q. Liu, Y. Zhou, Z. Yue, B. Barua and Y. Zhang, "Optimal Pricing Strategy for Residential Electricity Usage in Smart Grid," 2019 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm), Beijing, China, 2019, pp. 1-6, doi: 10.1109/SmartGridComm.2019.8909769
Optimal pricing strategy for residential electricity usage in smart grid
|Author:||Liu, Quan-Hui1; Zhou, Yingjie2; Yue, Zhongtao1;|
1CompleX Lab, School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, Sichuan, China, 611731
2College of Computer Science, Sichuan University, Chengdu, Sichuan, China, 610065
3Centre for Wireless Communications, University of Oulu, Oulu, Finland, 90014
|Online Access:||PDF Full Text (PDF, 0.2 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe2020060841156
Institute of Electrical and Electronics Engineers,
|Publish Date:|| 2020-06-08
Electricity Retailers offer various utility plans in the hope that the increased competition would result in lower prices, improved service, and innovative product offerings. In this paper, we present the retail electric provider’s (REP) optimal pricing strategy for residential customers in smart grid, in which the REP offers multiple utility plans for customers with different needs, which includes a flat-rate plan, a multi-stage plan, and a lump-sum fee plan. The residential customers select the utility plan that maximize their own payoffs by considering their own demands and the pricing strategies of the three plans. In the other way around, the REP optimizes its profit by carefully designing its pricing strategy based on residential customers’ decisions. To obtain insights of such a highly coupled system, we consider a system with one REP and a group of customers in need of electricity. We propose a three-stage Stackelberg game model, in which the REP acts as the leader who decides the specific plans to offer at Stage I, then announces the price for each plan in stage II, and finally the customers act as followers that select plans in stage III. We derive the market equilibrium by analyzing customers’ decisions among the plans under different pricing schemes. Then, we provide the RP’s optimal pricing strategies to maximize its profit. In the end, we give the optimal decisions for REP on the specific plan(s) to offer while considering each customer’s evaluation and demand. Both the analytical and simulation results show that the lump-sum fee plan can maximize RP’s profit in most cases.
|Pages:||1 - 6|
2019 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids, SmartGridComm 2019, 21-23 October, Beijing, China
IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids
|Type of Publication:||
A4 Article in conference proceedings
|Field of Science:||
213 Electronic, automation and communications engineering, electronics
The work of Yingjie Zhou is partly supported by National Natural Science Foundation of China (NSFC) with grant number 61801315.
© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.