Abstract This paper uses quantile regression to demonstrate how electricity price distributions are linked to fundamental supply and demand variables. It investigates the California electricity market (zone SP15) for selected trading hours using data from January 8, 2013 to September 24, 2016. The approach quantifies a non-linear relationship between the fundamentals and electricity prices, just as predicted by the merit order curve. Natural gas, greenhouse gas allowance prices and load all have a positive effect on electricity prices, with the effect increasing with the quantiles. In contrast, solar production and wind production both have a negative effect on electricity prices. The effect of solar production increases with quantiles, whereas the effect of wind production decreases with quantiles. This paper also includes a stress testing case study in which a producer faces the risk of high solar and wind production, and investigates the effect on the lower tail of the price distribution. Overall, the results demonstrate how the proposed approach can be a helpful risk management tool for participants in the electricity market.

中文翻译：

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使用分位数回归进行价格情景分析和压力测试：加利福尼亚电力市场的案例研究

摘要 本文使用分位数回归来说明电价分布如何与基本供需变量相关联。它使用 2013 年 1 月 8 日至 2016 年 9 月 24 日的数据调查了加利福尼亚电力市场（SP15 区）的选定交易时间。该方法量化了基本面和电价之间的非线性关系，正如优先顺序曲线所预测的那样. 天然气、温室气体配额价格和负荷均对电价有正向影响，且影响随分位数增加。相比之下，太阳能生产和风能生产都对电价产生负面影响。太阳能发电的影响随分位数增加，而风力发电的影响随分位数减少。本文还包括一个压力测试案例研究，其中生产商面临太阳能和风能产量高的风险，并调查对价格分布下尾的影响。总体而言，结果表明所提出的方法如何成为电力市场参与者有用的风险管理工具。