Automated Negotiation for Peer-to-Peer Electricity Trading in Local Energy Markets

Christie Etukudor, Benoit Couraud, Valentin Robu, Wolf-Gerrit Fruh, David Flynn, Chinonso Okereke

Research output: Contribution to journalArticlepeer-review

20 Citations (Scopus)
54 Downloads (Pure)


Reliable access to electricity is still a challenge in many developing countries. Indeed, rural areas in sub-Saharan Africa and developing countries such as India still encounter frequent power outages. Local energy markets (LEMs) have emerged as a low-cost solution enabling prosumers with power supply systems such as solar PV to sell their surplus of energy to other members of the local community. This paper proposes a one-to-one automated negotiation framework for peer-to-peer (P2P) local trading of electricity. Our framework uses an autonomous agent model to capture the preferences of both an electricity seller (consumer) and buyer (small local generator or prosumer), in terms of price and electricity quantities to be traded in different periods throughout a day. We develop a bilateral negotiation framework based on the well-known Rubinstein alternating offers protocol, in which the quantity of electricity and the price for different periods are aggregated into daily packages and negotiated between the buyer and seller agent. The framework is then implemented experimentally, with buyers and sellers adopting different negotiation strategies based on negotiation concession algorithms, such as linear heuristic or Boulware. Results show that this framework and agents modelling allow prosumers to increase their revenue while providing electricity access to the community at low cost.
Original languageEnglish
Article number920
Issue number4
Publication statusPublished - 19 Feb 2020


  • Automated negotiation
  • Bilateral energy negotiations
  • Local electricity markets
  • Local energy markets
  • Multi-agent systems
  • P2P electricity trading

ASJC Scopus subject areas

  • Renewable Energy, Sustainability and the Environment
  • Energy Engineering and Power Technology
  • Energy (miscellaneous)
  • Control and Optimization
  • Electrical and Electronic Engineering


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