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Privacy Preserving Distributed Energy Trading

机译：隐私保留分布式能源交易

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摘要

The smart grid incentivizes distributed agents with local generation (e.g., smart homes, and microgrids) to establish multi-agent systems for enhanced reliability and energy consumption efficiency. Distributed energy trading has emerged as one of the most important multi-agent systems on the power grid by enabling agents to sell their excessive local energy to each other or back to the grid. However, it requests all the agents to disclose their sensitive data (e.g., each agent's fine-grained local generation and demand load). In this paper, to the best of our knowledge, we propose the first privacy preserving distributed energy trading framework, Private Energy Market (PEM), in which all the agents privately compute an optimal price for their trading (ensured by a Nash Equilibrium), and allocate pairwise energy trading amounts without disclosing sensitive data (via novel cryptographic protocols). Specifically, we model the trading problem as a non-cooperative Stackelberg game for all the agents (i.e., buyers and sellers) to determine the optimal price, and then derive the pairwise trading amounts. Our PEM framework can privately perform all the computations among all the agents without a trusted third party. We prove the privacy, individual rationality, and incentive compatibility for the PEM framework. Finally, we conduct experiments on real datasets to validate the effectiveness and efficiency of the PEM.
机译：智能电网刺激行为分布与局部产生（例如，智能家庭，和微网）代理商建立多代理系统用于增强的可靠性和能源消耗效率。分布式能源贸易已经使座席其过度当地能源出售给对方或者回给电网成为对电网最重要的多代理系统之一。然而，它要求所有的代理商透露他们的敏感数据（例如，每个代理的细粒度本地生产需求负荷）。在本文中，据我们所知，我们建议先隐私保护分布式能源的贸易框架，私营能源市场（PEM），其中所有的代理商私下计算用于交易的最优价格（由纳什均衡保证），和分配成对能源交易量而不公开敏感数据（通过新颖的密码协议）。具体来说，我们模拟交易问题作为一个非合作的Stackelberg游戏所有的药剂（即，买家和卖家），以确定最佳价格，然后派生成对的交易金额。我们PEM框架可以私下都没有一个可信的第三方代理中执行所有的计算。我们证明了隐私，个人理性，并为PEM框架激励相容。最后，我们对真实数据集进行实验来验证PEM的有效性和效率。

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