A Privacy-Preserving Blockchain-Based Method to Optimize Energy Trading
Jian Ping, Zheng Yan, Sijie Chen
Abstract
It is always desired for optimizing energy trading to disable manipulation and preserve individual privacy. These two features become increasingly appealing for an energy market where interest parties do not mutually trust each other, such as peer-to-peer energy trading. Traditional centralized or hierarchical optimization schemes are vulnerable to an untrusted coordinator who may dishonestly broadcast coordination results or be curious about individual privacy. Recent blockchain-based optimization schemes resist dishonesty but increase the risk of privacy leakage. This paper proposes a privacy-preserving blockchain-based method to optimize energy trading. In the proposed method, participants submit encrypted bids/offers based on a bid/offer encryption algorithm to preserve their privacy. A privacy-preserving-Byzantine-fault-tolerance-based coordination algorithm is proposed to ensure the correctness of trading results with considering dishonesty. Numerical results in a peer-to-peer energy trading case demonstrate the performance of our method on convergence, resisting dishonesty, preserving privacy, and scalability.