A real-time, personalized consumption-based pricing scheme for the consumptions of traditional and renewable energies

Yeming DAI*, Xilian SUN, Yao QI, Mingming LENG

*Corresponding author for this work

Research output: Journal PublicationsJournal Article (refereed)peer-review

13 Citations (Scopus)

Abstract

A real-time, personalized consumption-based pricing scheme can induce electricity users to change their purchase behaviors, thus becoming an important issue in exploring the management mechanisms of electricity markets. To stabilize electricity prices, increase operators' revenues, and balance market demands, we consider the pricing scheme in a smart grid market where traditional and renewable energies are available for sales. Under the scheme, we develop a leader-follower game to characterize the strategic interactions between a demand side management center and residential users, and show that there exists a unique Stackelberg equilibrium. Our numerical analysis indicates that the real-time pricing scheme makes the electricity price difference between valley and peak times within 0.4 cents, thereby achieving the goal of mitigating peak loads and stabilizing electricity prices. We reveal that the renewable energy loads dominate traditional energy loads even when the price of renewable energy is higher than that of traditional energy. We also perform sensitivity analysis and find that an increase in a user's dissatisfaction with the electricity supply can raise electricity price for the user and two different electricity loads. Moreover, the demand side management center's revenue changes with a concave appearance.
Original languageEnglish
Pages (from-to)452-466
Number of pages15
JournalRenewable Energy
Volume180
Early online date25 Aug 2021
DOIs
Publication statusPublished - Dec 2021

Bibliographical note

Publisher Copyright:
© 2021 Elsevier Ltd

Funding

This work was supported by the National Natural Science Foundation of China [No. 71571108 ], Ministry of Education Layout Foundation of Humanities and Social Science [No. 20YJA630009 ], China Postdoctoral Science Foundation [No. 2016M602104 ], Qingdao Postdoctoral Application Research Funded Project [No. 2016033 ]. The fourth author (Mingming Leng) was supported by the Faculty research Grant of Lingnan University under the grant number DB20A1.

Keywords

  • Real-time pricing
  • Leader-follower game
  • Smart grid
  • Personalized consumption

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