Bilateral negotiations for electricity market by adaptive agent-tracking strategy

Kashif Imran, Jiangfeng Zhang, Anamitra Pal, Abraiz Khattak, Kafait Ullah, Sherjeel Mahmood Baig

Research output: Contribution to journalArticlepeer-review

13 Scopus citations


Bilateral transactions hedge both sides against uncertain price and volume risks of day-ahead auction and make up major portions of trading in electricity markets. Peer-to-peer bilateral transactions avoid broker fees but involve challenges of balancing between cooperative and competitive strategies for multi-round negotiations. To solve these challenges, this paper develops novel utility-based and adaptive agent-tracking strategies for bilateral negotiations. Relying on bilateral transaction volume and utility curves determined over a price range during unilateral pre-negotiation, utility-based strategies are developed for generation company (GenCo) agent (load serving entity (LSE) agent) to offer (bid) volumes and prices during multi-round bilateral negotiations. GenCo agent is also equipped with a new adaptive agent-tracking strategy that estimates reservation price of each LSE agent by Bayesian learning and updates the estimates in each round. The adaptive agent-tracking strategy facilitates cooperative yet competitive responses. Integration of new bilateral negotiation strategies with existing day-ahead auction in a renowned agent-based platform also enables combined simulation of the two market types. The case study demonstrates that the adaptive agent-tracking strategy empowers GenCoagents to swing bilateral negotiation results in their favor and yield 7% more payoff than the utility-based strategy, while achieving 100% improvement in frequency of failure of negotiation.

Original languageEnglish (US)
Article number106390
JournalElectric Power Systems Research
StatePublished - Sep 2020


  • Bilateral negotiations Day-ahead markets Peer-to-peer bilateral transactions Machine learning Heuristic methods Adaptive agents Agent-based models

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering


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