Optimal Selection of Trading Partner in Peer-to-Peer Energy Markets

Peer-to-Peer (P2P) energy trading in smart grids offers a promising solution to mitigate <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$CO_2$</tex> emissions. The success of a P2P energy market hinges on participants' involvement, which is significantly influenced by effective trading partner selection that ensures both energy bill savings for buyers and profitability for sellers. This paper proposes a model that optimizes trading partner selection to enhance participant utilities. The model considers various factors, including prices, quality of energy, confidence in energy delivery, and the supply-to-demand ratio (SDR). Our approach evaluates 11 energy sellers (ESs) and 11 energy consumers (ECs) over a one-year dataset, comparing the proposed model with an existing model from the literature. Results demonstrate that our model increases both revenue for ESs and savings in energy bills for ECs, outperforming the benchmark model. This study underscores the importance of optimal trading partner selection in achieving fair and efficient energy markets, ultimately contributing to the broader goal of sustainable energy management.