Truncated Strategy Based Dynamic Network Pricing for Energy Storage

Xiaohe Yan, Hongcai Zhang, Chenghong Gu, Nian Liu, Furong Li, Yonghua Song

Research output: Contribution to journalArticlepeer-review

1 Citation (SciVal)

Abstract

With the increasing penetration of local renewable energy and flexible demand, the system demand is more unpredictable and causes network overloading, resulting in costly system investment. Although the energy storage (ES) helps reduce the system peak power flow, the incentive for ES operation is not sufficient to reflect its value on the system investment deferral resulting from its operation. This paper designs a dynamic pricing signal for ES based on the truncated strategy under robust operation corresponding to the network charge reduction. Firstly, the operation strategy is designed for ES to reduce the total network investment cost considering the uncertainties of flexible load and renewable energy. These nodal uncertainties are converted into branch power flow uncertainties by the cumulant and Gram-Charlier expansion strategy. Then, a time of use (ToU) pricing scheme is designed to guide the ES operation reflecting its impact on network investment based on the long-run investment cost (LRIC) pricing scheme. The proposed ToU LRIC method allocates the investment costs averagely to network users over the potential curtailment periods, which connects the ES operation with network investment. The curtailment amount and the distribution of power flow are assessed by the truncated strategy considering the impact of uncertainties. As demonstrated in a Grid Supply Point (GSP) distribution network in the UK, the network charges at the peak time reduce more than 20% with ES operation. The proposed method is cost-reflective and ensures the fairness and efficiency of the pricing signal for ES.

Original languageEnglish
Pages (from-to)544-552
Number of pages9
JournalJournal of Modern Power Systems and Clean Energy
Volume11
Issue number2
Early online date14 Mar 2022
DOIs
Publication statusPublished - 31 Mar 2023

Bibliographical note

This work was supported by the National Natural Science Foundation of China (No. 52107090) and the Fundamental Research Funds for the Central Universities (No. JB2021007).

Keywords

  • Energy storage
  • network investment
  • renewable energy
  • robust optimization
  • uncertainty

ASJC Scopus subject areas

  • Renewable Energy, Sustainability and the Environment
  • Energy Engineering and Power Technology

Fingerprint

Dive into the research topics of 'Truncated Strategy Based Dynamic Network Pricing for Energy Storage'. Together they form a unique fingerprint.

Cite this