Journal of Shanghai Jiao Tong University

Journal of Shanghai Jiaotong University >

2025 , Vol. 59 >Issue 9: 1359 - 1369

DOI: https://doi.org/10.16183/j.cnki.jsjtu.2023.481

New Type Power System and the Integrated Energy

A Multi-Grade Pricing Strategy for Distributed Energy Storage Considering Default Risks of Customized Power Services

  • FANG Jun ,
  • HE De ,
  • PEI Zhigang ,
  • PENG Zhihui ,
  • BAO Jieying ,
  • LIU Weikang ,
  • ZHOU Bin
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  • 1 Shaoxing Power Supply Company, State Grid Zhejiang Electric Power Co., Ltd., Shaoxing 312000, Zhejiang, China
    2 College of Electrical and Information Engineering, Hunan University, Changsha 410082, China

Received date: 2023-09-21

  Revised date: 2023-10-20

  Accepted date: 2023-11-17

  Online published: 2023-11-23

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Abstract

To address the problems in the profit model and transaction pricing of distributed energy storage providing multiple customized power services for sensitive customers, a multi-grade pricing strategy for distributed energy storage to provide various customized power services is proposed, including reactive power compensation, voltage sag control, and harmonic control. First, based on the four-quadrant operation characteristics of energy storage converter, a multi-grade evaluation indicator system of customized power services is established considering the differentiated user demands for power quality. Then, a cost-to-capacity model is developed for energy storage to provide customized power services in different power quality standards. Next, by taking economic loss of power quality into account, a user customized power utility function is established with individual rational constraint. Afterwards, considering power quality default risk and investment cost constraints, a customized power revenue model of distributed energy storage is constructed. Furthermore, a multi-grade trading framework for distributed energy storage to provide differentiated customized power services and its multi-grade pricing optimization strategy are proposed. Finally, in order to obtain the optimal additional tariff and user purchase package for premium power, the nonlinear multi-grade pricing model is transformed into a mixed integer linear programming model for optimization by using the big M method and transforming the user utility function into a constraint. The comparative analysis of the algorithm demonstrates that the proposed strategy can reduce the annual cost of customized power services for users while simultaneously enhancing the energy storage revenue.

Key words： distributed energy storage; customized power; conditional value-at-risk; multi-grade pricing; mixed integer programming

Cite this article

FANG Jun , HE De , PEI Zhigang , PENG Zhihui , BAO Jieying , LIU Weikang , ZHOU Bin . A Multi-Grade Pricing Strategy for Distributed Energy Storage Considering Default Risks of Customized Power Services[J]. Journal of Shanghai Jiaotong University, 2025 , 59(9) : 1359 -1369 . DOI: 10.16183/j.cnki.jsjtu.2023.481

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