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

Abstract

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.

The Impact of Attacks in LEM and Prevention Measures Based on Forecasting and Trust Models

“…A LEM provides the main service of negotiation to its participants. This negotiation is offered as an iterative negotiation processes, where, in regular periods the participants have the opportunity to submit their proposals to buy or to sell energy, and agree on a market price in each period [8].…”

New Methods for Improved Prosumer Trading and Energy Poverty Mitigation in Microgrids using Crowdsourcing Concepts and Blockchain Technologies

“…Methodologies based on the remote sensing of the atmospheric conditions are the primary source of information for the development of numerical models that aim at supporting the planning and operation of an electric system with a substantial contribution of intermittent energy sources [49]. For local trading of such electricity surplus, the LEM operators consider the blockchain concept [11,12,16,28,29,40,41,48], or direct bilateral contracts [50,51]. These market models aim to provide secure and affordable energy supply for the end user, which is essential for the functioning of an economy in which energy poverty is reduced and the needs of vulnerable social groups are taken into account [52].…”

“Peer-to-Peer Plus” Electricity Transaction within Community of Active Energy Agents Regarding Distribution Network Constraints

“…By considering the distance between two nodes, sellers would give more power to buyers who is closer to them [7]. Reference [8] integrates the cost and quantity of electricity in the utility function to describe the agent's preference or value for an offer. Secondly, the negotiation refers to the strategies according to which the two parties in P2P transaction dynamically update their bids.…”

“…Reference [11] adopts an adaptive and aggressive trading strategy that reflects the willingness of market players in P2P energy trading. By using agent modelling to capture the preferences of entities, the impact of three negotiation strategies on transaction process are discussed in reference [8]. Most existing work offers the P2P market players with the principal one chance to select the counterparty.…”