A Novel Peer-to-Peer Local Electricity Market for Joint Trading of Energy and Uncertainty

Zhong Zhang, Ran Li, Furong Li

Research output: Contribution to journalArticlepeer-review

166 Citations (SciVal)


In the future power system, an increasing number of distributed energy resources will be integrated including intermittent generation like photovoltaic (PV) and flexible demand like electric vehicles (EVs). It has been long thought to utilize the flexible demand to absorb the PV output locally with the technical solution proposed while an effective commercial arrangement is yet to be developed due to the significant uncertainty associated with local generation. This paper proposes a peer-to-peer (P2P) local electricity market model incorporating both energy trading and uncertainty trading simultaneously. The novelty is to match the forecast power with demand having time flexibility and the uncertain power with demand having power flexibility. This market enables more PV uncertainty to be balanced locally rather than propagating to the upper layer system. In the test case, 55.3% of PV forecast error can be balanced locally in the proposed joint market. In comparison, 43.6% of PV forecast error is balanced locally when the forecast power and uncertain power are traded separately in a day-ahead market and a real-time market. The proposed P2P market can also motivate PV owners to improve forecast accuracy.

Original languageEnglish
Article number8789684
Pages (from-to)1205-1215
Number of pages11
JournalIEEE Transactions on Smart Grid
Issue number2
Early online date6 Aug 2019
Publication statusPublished - 31 Mar 2020


  • local trading model
  • Peer to peer market
  • power flexibility
  • time flexibility
  • uncertainty consumption

ASJC Scopus subject areas

  • General Computer Science


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