LMP-based Pricing for Energy Storage in Local Market to Facilitate PV Penetration

Xiaohe Yan, Chenghong Gu, Furong Li, Zhaoyu Wang

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Increasing Photovoltaic (PV) penetration and low-carbon demand can potentially lead to two different flow peaks, generation, and load, within distribution networks. This will not only constrain PV penetration but also pose serious threats to network reliability. This paper uses energy storage (ES) to reduce system congestion cost caused by the two peaks by sending cost-reflective economic signals to affect ES operation in responding to network conditions. First, a new charging and discharging (C/D) strategy based on binary search method is designed for ES, which responds to system congestion cost over time. Then, a novel pricing method, based on locational marginal pricing (LMP), is designed for ES. The pricing model is derived by evaluating ES impact on the network power flows and congestions from the loss and congestion components in LMP. The impact is then converted into an hourly economic signal to reflect ES operation. The proposed ES C/D strategy and pricing methods are validated on a real local grid supply point area. Results show that the proposed LMP-based pricing is efficient to capture the feature of ES and provide signals for affecting its operation. This work can further increase network flexibility and the capability of networks to accommodate increasing PV penetration.

Original languageEnglish
Pages (from-to)3373-3382
Number of pages10
JournalIEEE Transactions on Power Systems
Issue number3
Early online date19 Dec 2017
Publication statusPublished - 1 May 2018


  • Congestion management
  • DG consumption
  • Energy storage
  • energy storage
  • Investment
  • LMP
  • Load flow
  • Loading
  • Power system reliability
  • Pricing
  • pricing
  • Reliability

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering


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