# Privacy-Friendly Peer-to-Peer Energy Trading: A Game Theoretical Approach

arXiv: https://arxiv.org/abs/2201.01810 · HTML: https://mlsanity.com/paper/2201.01810/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 4 of its 19 references that are in the map.
- First posted on arXiv 5 Jan 2022.

## Builds on (most cited first, 4 of 4)

- [Peer-to-Peer Energy Trading with Sustainable User Participation: A Game Theoretic Approach](https://mlsanity.com/paper/1809.11034/) (2018)
- [A Game-Theoretic Approach to Energy Trading in the Smart Grid](https://mlsanity.com/paper/1310.1814/) (2013)
- [Secure and Privacy-Friendly Local Electricity Trading and Billing in Smart Grid](https://mlsanity.com/paper/1801.08354/) (2018)
- [Privacy Preserving Distributed Energy Trading](https://mlsanity.com/paper/2004.12216/) (2020)

## Abstract (arXiv)

In this paper, we propose a decentralized, privacy-friendly energy trading platform (PFET) based on game theoretical approach - specifically Stackelberg competition. Unlike existing trading schemes, PFET provides a competitive market in which prices and demands are determined based on competition, and computations are performed in a decentralized manner which does not rely on trusted third parties. It uses homomorphic encryption cryptosystem to encrypt sensitive information of buyers and sellers such as sellers' prices and buyers' demands. Buyers calculate total demand on particular seller using an encrypted data and sensitive buyer profile data is hidden from sellers. Hence, privacy of both sellers and buyers is preserved. Through privacy analysis and performance evaluation, we show that PFET preserves users' privacy in an efficient manner.