Decentralized PV Energy Trading: A Case Study of Residential Households in Qatar

Nassma Mohands*, Sertac Bayhan, Antonio Sanfilippo, Haitham Abu Rub

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

This paper describes a peer-to-peer (P2P) energy trading market framework based on game theory and agent-based modeling (ABM) that enables owners of photovoltaic (PV) systems to sell the electricity they produce to neighbors and the grid. Energy is traded at a rate determined by local energy producers and consumers. The energy price is dynamic and depends on changes in the generation-to-demand ratio throughout the day. The amount of excess energy produced is listed in the market by all available sellers, along with the generation type, price, and location. The market framework was tested using multiple scenarios, which were determined by including battery storage, reduction of subsidies for non-renewable energy, introduction of a carbon tax, and increasing PV capacity to study outcomes of solar PV trading. The results suggest that when greater PV capacity is assumed, the benefits of trading increase, and a larger proportion of household demand is met locally without the need to buy energy from the grid. Adding battery storage to the system enhances trading, provides more energy for sale, and reduces the amount of energy purchased from the grid. The model presented can be scaled up to model several neighborhoods or an entire city.

Original languageEnglish
Pages (from-to)153457-153470
Number of pages14
JournalIEEE Access
Volume12
DOIs
Publication statusPublished - 14 Oct 2024

Keywords

  • Agent-based modeling
  • Batteries
  • Buildings
  • Costs
  • Data models
  • Distributed power generation
  • Electricity
  • Electricity market
  • Energy exchange
  • Evolutionary game
  • Game theoretical models
  • Game theory
  • Games
  • M-leader
  • N-follower Stackelberg game
  • Renewable energy sources
  • peer-to-peer trading (P2P)

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