In this paper, we study a general transactive energy (TE) retailing problem in smart grids: a TE retailer (e.g., a utility company) publishes the energy price, which may vary over time. TE customers arrive in an arbitrary manner and may choose to either purchase a certain amount of energy based on the posted price, or leave without buying. Typical examples of such a setup include a transactive electric vehicle charging platform, or a general market-based demand-side management program, etc. We consider the setting where the customer arrival information is unknown (i.e., without prediction), and focus on maximizing the social welfare of the TE system through a posted-price mechanism (PPM) that runs in an online fashion with causal information only. We quantify the performance of the proposed PPM in the competitive analysis framework, and show that our proposed PPM is optimal in the sense that no other online mechanisms can achieve a better competitive ratio. We evaluate our theoretic results for the case of transactive electric vehicle charging. Our extensive experimental results show that the proposed PPM is competitive and robust against system uncertainties, and outperforms several existing benchmarks.

中文翻译：

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交易性能源的后价零售：一种没有预测的最优在线机制

在本文中，我们研究了智能电网中的一般交易性能源 (TE) 零售问题：TE 零售商（例如，公用事业公司）发布了可能随时间变化的能源价格。TE 客户以任意方式到达，可以选择根据公布的价格购买一定数量的能源，或者不购买就离开。这种设置的典型例子包括交互性电动汽车充电平台，或基于市场的通用需求侧管理程序等。我们考虑客户到达信息未知（即没有预测）的设置，并专注于最大化TE 系统的社会福利通过以仅具有因果信息的在线方式运行的张贴价格机制 (PPM)。我们在竞争分析框架中量化了提议的 PPM 的性能，并表明我们提出的 PPM 是最优的，因为没有其他在线机制可以实现更好的竞争比率。我们评估了交互电动汽车充电案例的理论结果。我们广泛的实验结果表明，所提出的 PPM 对系统不确定性具有竞争力和鲁棒性，并且优于几个现有的基准。