Design and simulation of peer-to-peer energy trading framework with dynamic electricity price

Bidan Zhang, Yang Du, Eng Gee Lim, Lin Jiang, Ke Yan

Research output: Chapter in Book or Report/Conference proceedingConference Proceedingpeer-review

16 Citations (Scopus)

Abstract

Peer-to-Peer (P2P) market scheme enables the individual participant to trade surplus electricity generated by rooftop photovoltaic (PV) with their neighbors. It is an effective way to manage distributed generation (DG) and promote demand response. In this paper, we proposed a P2P trading framework with consideration of the dynamic retail electricity price for the first time. The prosumers can use the decision-making model proposed in this framework to automatically generate bids and participate in the auction in the P2P market. Simulation has been built in MATLAB to evaluate the performance of three pricing models: Double Auction (DA), Mid-Market Rate (MMR) and Supply and Demand Ratio (SDR). Simulation results show that P2P energy trading can bring economic and technical benefits to participants. It is also able to improve the local balance of energy generation and consumption.

Original languageEnglish
Title of host publication2019 29th Australasian Universities Power Engineering Conference, AUPEC 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728150437
DOIs
Publication statusPublished - Nov 2019
Event29th Australasian Universities Power Engineering Conference, AUPEC 2019 - Nadi, Fiji
Duration: 26 Nov 201929 Nov 2019

Publication series

Name2019 29th Australasian Universities Power Engineering Conference, AUPEC 2019

Conference

Conference29th Australasian Universities Power Engineering Conference, AUPEC 2019
Country/TerritoryFiji
CityNadi
Period26/11/1929/11/19

Keywords

  • Battery control strategy
  • Clearing pricing mechanism
  • Distributed energy resources
  • Dynamic electricity price
  • Peer-to-Peer energy trading
  • Power market

Fingerprint

Dive into the research topics of 'Design and simulation of peer-to-peer energy trading framework with dynamic electricity price'. Together they form a unique fingerprint.

Cite this