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Towards Efficient and Secured Real-time Pricing in the Smart Grid

机译：迈向智能电网的高效和安全实时定价

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In this paper, we investigate a novel real-time pricing scheme, which considers both renewable energy resources and traditional power resources, and can effectively guide the participants to achieve individual welfare maximization. Particularly, we develop a Lagrangian-based approach that transforms the global optimization conducted by the power company to distributed optimization problems. We show that these distributed problems are consistent with individual welfare maximization problems for end-users and traditional power plants. We also investigate vulnerabilities of the real-time pricing scheme by considering two types of data integrity attacks, i.e., injecting false data into demand-users and injecting false data into supply-users. Through a combination of theoretical analysis and performance evaluation, our data shows that the proposed real-time pricing scheme can effectively guide the participants to achieve welfare maximization. Our data also shows that data integrity attacks can effectively disrupt the results of real-time pricing decisions, posing welfare reduction on participants.
机译：在本文中，我们调查了一种新的实时定价计划，其考虑可再生能源资源和传统的电力资源，并有效引导参与者实现个人福利最大化。特别是，我们开发了一种基于拉格朗日的方法，将电力公司进行的全球优化转变为分布式优化问题。我们表明，这些分布式问题与最终用户和传统发电厂的个人福利最大化问题一致。我们还通过考虑两种类型的数据完整性攻击，即将假数据注入需求用户并将错误数据注入供应用户来调查实时定价方案的漏洞。通过理论分析和绩效评估的组合，我们的数据表明，建议的实时定价方案可以有效地指导参与者实现福利最大化。我们的数据还显示数据完整性攻击可以有效地破坏实时定价决策的结果，造成参与者的福利减少。

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