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Various peer-to-peer energy markets have emerged in recent years in anattempt to manage distributed energy resources in a more efficient way. One ofthe main challenges these models face is how to create and allocate incentivesto participants. Cooperative game theory offers a methodology to financiallyreward prosumers based on their contributions made to the local energycoalition using the Shapley value, but its high computational complexity limitsthe size of the game. This paper explores a stratified sampling method proposedin existing literature for Shapley value estimation, and modifies the methodfor a peer-to-peer cooperative game to improve its scalability. Finally,selected case studies verify the effectiveness of the proposed coalitionalstratified random sampling method and demonstrate results from large games.

Estimation of the Shapley Value of a Peer-to-Peer Energy Sharing Game using Coalitional Stratified Random Sampling