电力市场中大型灵活加密货币挖矿消费者的计量经济学分析
An Econometric Analysis of Large Flexible Cryptocurrency-mining Consumers in Electricity Markets
AI总结：
本文通过计量经济学方法分析德克萨斯州大型加密货币挖矿企业的用电行为，发现短期用电主要受温度和电价而非币价影响，并提出了可用于电网影响评估与定价机制优化的用电模型。
摘要：
近年来，电网中出现了大量大型加密货币挖矿企业，其个体用电水平已达到700MW。本研究考察了这些企业在德克萨斯州的行为，重点关注其用电量如何受到加密货币兑换率、电价、当地天气及其他因素的影响。我们对这些企业呈偏态分布的用电数据进行了变换，开展了相关性分析，并应用季节性自回归移动平均模型进行分析。我们的研究结果表明，令人意外的是，短期挖矿用电量与加密货币兑换率并不直接相关。相反，主要影响因素是温度和电价。这些企业还会在夏季月份做出响应，以避免输配电网络（T&D）费用——通常称为四次同步峰值（4CP）费用。由于这些企业的规模在未来几年可能大幅增长，所建立的用电量模型可用于生成公开的合成数据集，以了解其对电网的整体影响。所建立的模型还有助于设计更好的定价机制，从而有效利用这些资源的灵活性来提高电网可靠性。
英文摘要：
In recent years, power grids have seen a surge in large cryptocurrency mining firms, with individual consumption levels reaching 700MW. This study examines the behavior of these firms in Texas, focusing on how their consumption is influenced by cryptocurrency conversion rates, electricity prices, local weather, and other factors. We transform the skewed electricity consumption data of these firms, perform correlation analysis, and apply a seasonal autoregressive moving average model for analysis. Our findings reveal that, surprisingly, short-term mining electricity consumption is not directly correlated with cryptocurrency conversion rates. Instead, the primary influencers are the temperature and electricity prices. These firms also respond to avoid transmission and distribution network (T&D) charges - commonly referred to as four Coincident peak (4CP) charges - during the summer months. As the scale of these firms is likely to surge in future years, the developed electricity consumption model can be used to generate public, synthetic datasets to understand the overall impact on the power grid. The developed model could also lead to better pricing mechanisms to effectively use the flexibility of these resources towards improving power grid reliability.
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